Relevant bibliographies by topics / Reward Processing

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Reward Processing'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 July 2025

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Journal articles on the topic "Reward Processing"

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Greene, Rachel K., Cara R. Damiano-Goodwin, Erin Walsh, Joshua Bizzell, and Gabriel S. Dichter. "Neural Mechanisms of Vicarious Reward Processing in Adults with Autism Spectrum Disorder." Autism Research and Treatment 2020 (March 21, 2020): 1–12. http://dx.doi.org/10.1155/2020/8014248.

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Previous studies examining the neural substrates of reward processing in ASD have explored responses to rewards for oneself but not rewards earned for others (i.e., vicarious reward). This omission is notable given that vicarious reward processing is a critical component of creating and maintaining social relationships. The current study examined the neural mechanisms of vicarious reward processing in 15 adults with ASD and 15 age- and gender-matched typically developing controls. Individuals with ASD demonstrated attenuated activation of reward-related regions during vicarious reward processi
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Sutcubasi Kaya, B., B. Metin, F. Z. Krzan, N. Tarhan, and C. Tas. "The Relationship Between Responsiveness to Social and Monetary Rewards and ADHD Symptoms." European Psychiatry 41, S1 (2017): S635. http://dx.doi.org/10.1016/j.eurpsy.2017.01.1041.

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IntroductionAlterations in reward processing are frequently reported in ADHD. One important factor that affects reward processing is the quality of reward, as social and monetary, rewards are processed by different neural networks. However, effect of reward type on reward processing in ADHD was not extensively studied.AimsWe aimed to explore the effect of reward type (i.e., social or monetary) on different phases of reward processing and also to test the hypothesis that ADHD symptoms may be associated with a problem in processing of social rewards.MethodsWe recorded event-related potentials (E
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Wang, Zhao, Qi Li, Lu Nie, and Ya Zheng. "Neural dynamics of monetary and social reward processing in social anhedonia." Social Cognitive and Affective Neuroscience 15, no. 9 (2020): 991–1003. http://dx.doi.org/10.1093/scan/nsaa128.

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Abstract Being characterized by reduced pleasure from social interaction, social anhedonia constitutes a transdiagnostic marker for various psychiatric disorders. However, the neural portrait of social anhedonia remains elusive because of heterogeneities of reward type and reward dynamics in previous studies. The present event-related potential study investigated neural dynamics in response to monetary and social rewards in social anhedonia. Event-related potential responses were examined when a high social anhedonia (HSA, N = 23) group and a low social anhedonia (LSA, N = 26) group were antic
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Metin, Baris, Zeynep C. Tas, Merve Çebi, et al. "Reward Processing Deficits During a Spatial Attention Task in Patients With ADHD: An fMRI Study." Journal of Attention Disorders 22, no. 7 (2017): 694–702. http://dx.doi.org/10.1177/1087054717703188.

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Objective: In this study, we aimed to explore how cues signaling rewards and feedbacks about rewards are processed in ADHD. Method: Inside the scanner, 16 healthy children and 19 children with ADHD completed a spatial attention paradigm where cues informed about the availability of reward and feedbacks were provided about the earned reward. Results: In ventral anterior thalamus (VA), the controls exhibited greater activation in response to reward-predicting cues, as compared with no-reward cues, whereby in the ADHD group, the reverse pattern was observed (nonreward > reward). For feedbacks;
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Clark, Andrew M. "Reward processing: a global brain phenomenon?" Journal of Neurophysiology 109, no. 1 (2013): 1–4. http://dx.doi.org/10.1152/jn.00070.2012.

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Rewards and punishments (reinforcement) powerfully shape behavior. Accordingly, their neuronal representation is of significant interest, both for understanding normal brain-behavior relationships and the pathophysiology of disorders such as depression and addiction. A recent article by Vickery and colleagues ( Neuron 72: 166–177, 2011) provides evidence that the neural response to rewards and punishments is surprisingly widespread, suggesting the need for examination of the specific roles of areas not commonly included in the canonical reward circuitry in processing reinforcement.
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Weinberg, Anna, and Stewart A. Shankman. "Blunted Reward Processing in Remitted Melancholic Depression." Clinical Psychological Science 5, no. 1 (2016): 14–25. http://dx.doi.org/10.1177/2167702616633158.

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Blunted reward response appears to be a trait-like marker of vulnerability for major depressive disorder (MDD). As such, it should be present in remitted individuals; however, depression is a heterogeneous syndrome. Reward-related impairments may be more pronounced in individuals with melancholic depression. The present study examined neural responses to rewards in remitted melancholic depression (rMD; n = 29), remitted nonmelancholic depression (rNMD; n = 56), and healthy controls (HC; n = 81). Event-related potentials to monetary gain and loss were recorded during a simple gambling paradigm.
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Schultz, W. "Neuronal reward processing." Appetite 57 (July 2011): S39. http://dx.doi.org/10.1016/j.appet.2011.05.265.

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Wang, Lingxiao, Guochun Yang, Ya Zheng, et al. "Enhanced neural responses in specific phases of reward processing in individuals with Internet gaming disorder." Journal of Behavioral Addictions 10, no. 1 (2021): 99–111. http://dx.doi.org/10.1556/2006.2021.00003.

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AbstractBackground and aimsInternet gaming disorder (IGD) has become a global health problem. The self-regulation model noted that a shift to reward system, whether due to overwhelming reward-seeking or impaired control, can lead to self-regulation failures, e.g., addiction. The present study focused on the reward processing of IGD, aiming to provide insights into the etiology of IGD. Reward processing includes three phases: reward anticipation, outcome monitoring and choice evaluation. However, it is not clear which phases of reward processing are different between individuals with IGD and he
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Bermudez, Maria A., and Wolfram Schultz. "Timing in reward and decision processes." Philosophical Transactions of the Royal Society B: Biological Sciences 369, no. 1637 (2014): 20120468. http://dx.doi.org/10.1098/rstb.2012.0468.

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Sensitivity to time, including the time of reward, guides the behaviour of all organisms. Recent research suggests that all major reward structures of the brain process the time of reward occurrence, including midbrain dopamine neurons, striatum, frontal cortex and amygdala. Neuronal reward responses in dopamine neurons, striatum and frontal cortex show temporal discounting of reward value. The prediction error signal of dopamine neurons includes the predicted time of rewards. Neurons in the striatum, frontal cortex and amygdala show responses to reward delivery and activities anticipating rew
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Yuan, Yiran. "The Atypical Neural Processing of Reward in Bipolar Disorder." Communications in Humanities Research 50, no. 1 (2024): 118–24. http://dx.doi.org/10.54254/2753-7064/50/20242510.

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Abstract: There are still many unanswered questions regarding bipolar disorder among researchers. Understanding the characteristics of a particular area and neuroeconomics can aid in a more thorough examination of reward dysfunction and the reward process. Because changes in reward are undoubtedly one of the most prevalent signs of psychopathology in humans, researchers try to understand the prevalence of these diseases as well as the importance of reward in the manifestation of these conditions. Research indicates that different biological entities with comparable phenotypic symptoms make up
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Dissertations / Theses on the topic "Reward Processing"

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Manohar, S. G. "Frontostriatal contributions to reward processing." Thesis, University College London (University of London), 2015. http://discovery.ucl.ac.uk/1470430/.

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Dopaminergic projections to striatum and prefrontal cortex are thought to signal rewards, thereby energising movement, facilitating learning, and motivating effort. Extensive evidence links reward to attention and to dopamine. However a direct characterisation of how dopamine influences reward sensitivity in humans is lacking. This thesis examines the effects of dopamine and reward on eye movements. First, I introduced incentive manipulations into an “oculomotor capture” task, in which involuntary saccades are generated towards salient distractors. Whereas rewards increased both speed and accu
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Crawford, Bonni. "Social reward and threat processing." Thesis, Cardiff University, 2015. http://orca.cf.ac.uk/90984/.

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The aim of this project was to investigate the relationships between individual differences in social expectancies and motivation, and how these relate to broader personality traits and to social integration outcomes such as individuals’ sense of belonging. A cognitive model of social motivation and reactivity to social feedback was proposed. In this model, generalised expectancies are considered to play a pivotal role in motivating human social behaviour. Two novel measures were developed: the levels of dispositional expectancies of social threat and reward scale (the LODESTARS) and a task-ba
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Nymberg, Charlotte. "The neurobiology of reward processing in adolescence." Thesis, King's College London (University of London), 2013. https://kclpure.kcl.ac.uk/portal/en/theses/the-neurobiology-of-reward-processing-in-adolescence(e9ad0c43-b66b-4336-801d-d63c1b475914).html.

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Adolescence represents a time in development when the reward system undergoes substantial changes. Several studies suggest differences in reward processing amongst adolescents compared to adults and children. Abnormalities in reward processing also underlie many psychiatric disorders, such as attention deficit hyperactivity disorder (ADHD). The present research has the following objectives: 1) to investigate normal reward processing during reward anticipation and reward feedback in a large population based cohort of old adolescents. 2) to explore gender differences in reward processing and det
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Cowdrey, Felicity Ann. "Rumination and reward processing in anorexia nervosa." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:1d86eb13-7d41-40ef-a347-6480ebfefeb2.

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Anorexia nervosa (AN) is an eating disorder characterised by severe emaciation due deliberate restriction of food intake and an intense fear of gaining weight. Theoretical accounts of AN have to date focused predominately on cognitive elements of the disorder, yet resulting treatments have been inadequate and outcome for AN remains poor. Understanding the processes that maintain the disorder is an important step in developing effective strategies to augment existing treatments. With this in mind, the question arises: what processes drive AN? Novel frameworks for AN suggest that particular info
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McGraw, Justin James. "Reward processing alterations for natural reward in alcohol-preferring (P) rats: Incentive contrast, reward discrimination, and alcohol consumption." Bowling Green State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1526310548842931.

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Morgan, Joanne E. "Antisocial behaviour in adolescence : the role of reward processing." Thesis, Cardiff University, 2012. http://orca.cf.ac.uk/44838/.

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Rewards are fundamental in directing our behaviour, yet maladaptive reward processing can lead to risky and impaired decision making. The nature of reward processing in individuals who display antisocial behaviour is poorly understood, particularly in adolescents. The present thesis examined reward processing in young male offenders involved in the criminal justice system. A multi-method approach to the examination of reward was adopted, using personality, neuropsychological and psychophysiological approaches. The heterogeneity of antisocial behaviour was explored by using self-report and offi
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Berghorst, Lisa Hinckley. "Examining the Relationships between Stress, Reward Processing, and Bipolar Disorder." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10479.

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Bipolar disorder (BD) is a prevalent illness associated with severe impairments in functioning and elusive etiological pathways. Although a strong link between negative life stress and the onset of mood episodes in BD has been documented, the mechanisms underlying this connection remain unclear. A dysregulated reward system may play a prominent role in bridging these phenomena given that anhedonia and hyperhedonia are often symptoms of BD. Furthermore, emerging research suggests that negative stress influences reward responsiveness and the neurobiological substrates that regulate this system.
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García-García, Isabel, Annette Horstmann, María Angeles Jurado, et al. "Reward processing in obesity, substance addiction and non-substance addiction." Universitätsbibliothek Leipzig, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-196512.

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Similarities and differences between obesity and addiction are a prominent topic of ongoing research. We conducted an activation likelihood estimation meta-analysis on 87 studies in order to map the functional magnetic resonance imaging (fMRI) response to reward in participants with obesity, substance addiction and non-substance (or behavioural) addiction, and to identify commonalities and differences between them. Our study confirms the existence of alterations during reward processing in obesity, non-substance addiction and substance addiction. Specifically, participants with obesity or with
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García-García, Isabel, Annette Horstmann, María Angeles Jurado, et al. "Reward processing in obesity, substance addiction and non-substance addiction." Obesity reviews 2014, 11: 853 - 869, 2014. https://ul.qucosa.de/id/qucosa%3A14428.

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Similarities and differences between obesity and addiction are a prominent topic of ongoing research. We conducted an activation likelihood estimation meta-analysis on 87 studies in order to map the functional magnetic resonance imaging (fMRI) response to reward in participants with obesity, substance addiction and non-substance (or behavioural) addiction, and to identify commonalities and differences between them. Our study confirms the existence of alterations during reward processing in obesity, non-substance addiction and substance addiction. Specifically, participants with obesity or with
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Häusler, Alexander Niklas [Verfasser]. "Neuroeconomic Foundations of Reward, Loss, and Risk Processing / Alexander Niklas Häusler." Bonn : Universitäts- und Landesbibliothek Bonn, 2019. http://d-nb.info/1179184475/34.

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Books on the topic "Reward Processing"

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W, Childs G. Using ReWire: Skill pack. Thomson Course Technology, 2008.

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Fried, Jason. Rework. Crown Business, 2010.

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Li, Qi, Arne Møller, and Xingchao Wang, eds. Cognitive Control and Reward Processing in Addiction. Frontiers Media SA, 2022. http://dx.doi.org/10.3389/978-2-88974-893-8.

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Ryan, Frank, and Nikolina Skandali, eds. Reward Processing in Motivational and Affective Disorders. Frontiers Media SA, 2016. http://dx.doi.org/10.3389/978-2-88919-986-0.

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Jarcho, Johanna M., Jason M. Chein, Amanda E. Guyer, Regina Marie Sullivan, and Marijn Van Wingerden, eds. Social and Non-Social Reward: Neural Mechanisms Implicated in Reward Processing Across Domains and Contexts. Frontiers Media SA, 2020. http://dx.doi.org/10.3389/978-2-88963-942-7.

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Bogdan, Ryan Henrichs. Genetic and environmental contributions to reward processing: Implications for depression. 2010.

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Zheng, Ya, Ruolei Gu, and Daniela M. Pfabigan, eds. Temporal Dynamics of Reward Processing in Humans: From Anticipation to Consummation. Frontiers Media SA, 2020. http://dx.doi.org/10.3389/978-2-88966-074-2.

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Hayes, Dave J., Georg Northoff, and Andrew J. Greenshaw, eds. Reward- and Aversion-Related Processing in the Brain: Translational Evidence for Separate and Shared Circuits. Frontiers Media SA, 2016. http://dx.doi.org/10.3389/978-2-88919-836-8.

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Young, Jared W., Alan Anticevic, and Deanna M. Barch. Cognitive and Motivational Neuroscience of Psychotic Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0016.

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Schizophrenia is a complex neuropsychiatric syndrome presenting with a constellation of symptoms. Clinicians have long recognized that abnormalities in cognitive function and motivated behavior are a key component of psychosis, and of schizophrenia in particular. Here we postulate that these deficits may reflect, at least in part, impairments in the ability to actively maintain and utilize internal representations of emotional experiences, previous rewards, and motivational goals in order to drive current and future behavior in a way that would normally allow individuals to obtain desired outc
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Nutt, David J., and Liam J. Nestor. Nicotine addiction. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198797746.003.0011.

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Cigarette smoking presents with considerable health risks and induces high costs on healthcare resources. People continue to smoke cigarettes in the face of adversity because they contain nicotine, which is highly addictive. Nicotine is a stimulant that exerts its effects within the brain by acting at nicotinic acetylcholine receptors (nAChRs). nAChRs are located in areas of the brain involved in reward processing, motivation, and cognitive control, which results in disruptions to behaviour when nicotine addiction has developed. Disturbances to the brain and behaviour are particularly evident
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Book chapters on the topic "Reward Processing"

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Beck, Anne, Anthony A. Grace, and Andreas Heinz. "Reward Processing." In Neuroimaging in Addiction. John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119998938.ch5.

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Chen, Chong, and Taiki Takahashi. "Reward Processing in Depression." In Computational Models of Brain and Behavior. John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119159193.ch5.

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Alba, Laura A., Elizabeth Baker, and Katherine K. M. Stavropoulos. "In Vivo Electrophysiology for Reward Anticipation and Processing." In The Brain Reward System. Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-1146-3_15.

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Kirby, Bridget, Ashley Dapore, Carl Ash, Kaitlyn Malley, and Robert West. "Smartphone Pathology, Agency and Reward Processing." In Information Systems and Neuroscience. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60073-0_37.

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Reinke, Chris, Eiji Uchibe, and Kenji Doya. "Average Reward Optimization with Multiple Discounting Reinforcement Learners." In Neural Information Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70087-8_81.

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Manoonpong, Poramate, Florentin Wörgötter, and Jun Morimoto. "Extraction of Reward-Related Feature Space Using Correlation-Based and Reward-Based Learning Methods." In Neural Information Processing. Theory and Algorithms. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-17537-4_51.

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Yang, Jiayuan, Yanjie Li, Haoyao Chen, and Jiangang Li. "Average Reward Reinforcement Learning for Semi-Markov Decision Processes." In Neural Information Processing. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-70087-8_79.

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Mahesan, Devu, Manisha Chawla, and Krishna P. Miyapuram. "The Effect of Reward Information on Perceptual Decision-Making." In Neural Information Processing. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46681-1_19.

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Asahina, Akiyo, Jun-ichiro Hirayama, and Shin Ishii. "Interpreting Dopamine Activities in Stochastic Reward Tasks." In Advances in Neuro-Information Processing. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02490-0_44.

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Mallorquí, Aida, Gonçalo Padrao, and Antoni Rodriguez-Fornells. "Electrophysiological Signatures of Reward Processing in Anhedonia." In Anhedonia: A Comprehensive Handbook Volume I. Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-8591-4_11.

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Conference papers on the topic "Reward Processing"

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Wu, Zhaofeng, Ananth Balashankar, Yoon Kim, Jacob Eisenstein, and Ahmad Beirami. "Reuse Your Rewards: Reward Model Transfer for Zero-Shot Cross-Lingual Alignment." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.79.

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Lee, Dong Won, Hae Won Park, Yoon Kim, Cynthia Breazeal, and Louis-Philippe Morency. "Global Reward to Local Rewards: Multimodal-Guided Decomposition for Improving Dialogue Agents." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.881.

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De Langis, Karin, Ryan Koo, and Dongyeop Kang. "Dynamic Multi-Reward Weighting for Multi-Style Controllable Generation." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.386.

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Zhu, Xinyi, Yanru Zhou, Dandan Song, and Ziyi Yang. "In-Context Learning Reward Guided Decoding for Controlled Text Generation." In 2024 9th International Conference on Intelligent Computing and Signal Processing (ICSP). IEEE, 2024. http://dx.doi.org/10.1109/icsp62122.2024.10743861.

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Lin, Tzu-Han, Chen-An Li, Hung-yi Lee, and Yun-Nung Chen. "DogeRM: Equipping Reward Models with Domain Knowledge through Model Merging." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.868.

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Cao, Shuirong, Ruoxi Cheng, and Zhiqiang Wang. "AGR: Age Group fairness Reward for Bias Mitigation in LLMs." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10890657.

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Chen, Lu, Rui Zheng, Binghai Wang, et al. "Improving Discriminative Capability of Reward Models in RLHF Using Contrastive Learning." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.852.

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Jiao, Fangkai, Chengwei Qin, Zhengyuan Liu, Nancy F. Chen, and Shafiq Joty. "Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.20.

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Lee, Younghwan, Tung M. Luu, Donghoon Lee, and Chang D. Yoo. "Reward Generation via Large Vision-Language Model in Offline Reinforcement Learning." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10889042.

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Li, Jiahui, Hanlin Zhang, Fengda Zhang, et al. "Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning." In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.emnlp-main.565.

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Reports on the topic "Reward Processing"

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Horne, R. E. Basis for Interim Operation (BIO) for the Rework Unit (RW), Du Pont Water (DW) Plant, Moderator Processing Facility (MPF), and Technical Purification Facility (TPF). Office of Scientific and Technical Information (OSTI), 1996. http://dx.doi.org/10.2172/656437.

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Veung, Naron, and Seyhah Ven. Exploring Insights into Vocational Skills Development and Industrial Transformation in Cambodia. Cambodia Development Resource Institute, 2021. https://doi.org/10.64202/wp.131.202110.

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Industrial development is central to Cambodia’s economic development as it plans to upgrade the country’s status to an upper-middle-income country by 2030 and to a high-income country by 2050. Equipping the workforce with the skills and competencies that match industrial needs requires a great deal of continuous efforts and resources. In this regard, this paper aims to look into the linkage between skills and transformation based on employers’ perspectives. It explores insights into how companies perceive and use the skills and qualifications of their employees to overcome changes in technolog
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