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Effective interlocutors account for the uncertain goals, beliefs, and emotions of others.
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Thin slices of negotiation: predicting outcomes from conversational dynamics within the first 5 minutes
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Reinforcement learning of argumentation dialogue policies in negotiation
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Echoes of power: Language effects and power differences in social interaction
Cristian Danescu-Niculescu-Mizil, Lillian Lee, Bo Pang, and Jon Kleinberg. 2012 · 2012
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Ioannis Efstathiou and Oliver Lemon. 2014 · 2014
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Trust region policy optimization
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Evaluating persuasion strategies and deep reinforcement learning methods for negotiation dialogue agents
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Deal or no deal? end-to-end learning of negotiation dialogues
Mike Lewis, Denis Yarats, Yann Dauphin, Devi Parikh, and Dhruv Batra. 2017 · 2017
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Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter. 2017 · 2017
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Proximal policy optimization algorithms
John Schulman, Filip Wolski, Prafulla Dhariwal, Alec Radford, and Oleg Klimov. 2017 · 2017
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Decoupling strategy and generation in negotiation dialogues
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Improving dialog systems for negotiation with personality modeling
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On the calibration of massively multilingual language models
Kabir Ahuja, Sunayana Sitaram, Sandipan Dandapat, and Monojit Choudhury. 2022 · 2022
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Opponent modeling in negotiation dialogues by related data adaptation
Kushal Chawla, Gale Lucas, Jonathan May, and Jonathan Gratch. 2022 · 2022
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Planning with theory of mind
Mark K Ho, Rebecca Saxe, and Fiery Cushman. 2022 · 2022
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Calibrating student models for emotion-related tasks
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Reinforcement learning: An introduction
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RL with KL penalties is better viewed as Bayesian inference
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Semantic uncertainty: Linguistic invariances for uncertainty estimation in natural language generation
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Answer-level calibration for free-form multiple choice question answering
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Teaching models to express their uncertainty in words
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Reducing conversational agents’ overconfidence through linguistic calibration
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Training language models to follow instructions with human feedback
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Expectation consistency for calibration of neural networks
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On the importance of exploration for generalization in reinforcement learning
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Forecasting earnings surprises from conference call transcripts
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Confidently wrong: Exploring the calibration and expression of (un)certainty of large language models in a multilingual setting
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Llama 2: Open foundation and fine-tuned chat models
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