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Aligning Large Language Models (LLMs) is crucial for enhancing their safety and utility.
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Generative adversarial imitation learning
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Proximal policy optimization algorithms
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Seqgan: Sequence generative adversarial nets with policy gradient
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Soft actor-critic algorithms and applications
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Deep q-learning from demonstrations
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Overcoming exploration in reinforcement learning with demonstrations
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Randomized prior functions for deep reinforcement learning
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Multi-goal reinforcement learning: Challenging robotics environments and request for research
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Extrapolating beyond suboptimal demonstrations via inverse reinforcement learning from observations
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Araml: A stable adversarial training framework for text generation
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Language models are unsupervised multitask learners
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Contrastive prefence learning: Learning from human feedback without rl
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Understanding the effects of rlhf on llm generalisation and diversity
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Privacy in large language models: Attacks, defenses and future directions
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Grandmaster level in starcraft ii using multi-agent reinforcement learning
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Towards a human-like open-domain chatbot
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D4rl: Datasets for deep data-driven reinforcement learning
Fu, J., Kumar, A., Nachum, O., Tucker, G., and Levine, S · 2020
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A divergence minimization perspective on imitation learning methods
Ghasemipour, S. K. S., Zemel, R., and Gu, S · 2020
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Strictly batch imitation learning by energy-based distribution matching
Jarrett, D., Bica, I., and van der Schaar, M · 2020
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A distributional approach to controlled text generation
Khalifa, M., Elsahar, H., and Dymetman, M · 2020
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Conservative q-learning for offline reinforcement learning
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Li, H., Chen, Y., Luo, J., Kang, Y., Zhang, X., Hu, Q., Chan, C., and Song, Y · 2023
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Nash learning from human feedback
Munos, R., Valko, M., Calandriello, D., Azar, M. G., Rowland, M., Guo, Z. D., Tang, Y., Geist, M., Mesnard, T., Michi, A., et al · 2023
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Direct preference optimization: Your language model is secretly a reward model
Rafailov, R., Sharma, A., Mitchell, E., Ermon, S., Manning, C. D., and Finn, C · 2023
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Accountable batched control with decision corpus
Sun, H., Hüyük, A., Jarrett, D., and van der Schaar, M · 2023
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Llama 2: Open foundation and fine-tuned chat models
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., et al · 2023
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Beyond reverse kl: Generalizing direct preference optimization with diverse divergence constraints
Wang, C., Jiang, Y., Yang, C., Liu, H., and Chen, Y · 2023
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Gibbs sampling from human feedback: A provable kl-constrained framework for rlhf
Xiong, W., Dong, H., Ye, C., Zhong, H., Jiang, N., and Zhang, T · 2023
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Towards robust offline reinforcement learning under diverse data corruption
Yang, R., Zhong, H., Xu, J., Zhang, A., Zhang, C., Han, L., and Zhang, T · 2023
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Rrhf: Rank responses to align language models with human feedback without tears
Yuan, Z., Yuan, H., Tan, C., Wang, W., Huang, S., and Huang, F · 2023
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Slic-hf: Sequence likelihood calibration with human feedback
Zhao, Y., Joshi, R., Liu, T., Khalman, M., Saleh, M., and Liu, P. J · 2023
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Secrets of rlhf in large language models part i: Ppo
Zheng, R., Dou, S., Gao, S., Hua, Y., Shen, W., Wang, B., Liu, Y., Jin, S., Liu, Q., Zhou, Y., et al · 2023
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Data quality in imitation learning
Belkhale, S., Cui, Y., and Sadigh, D · 2024
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Dense reward for free in reinforcement learning from human feedback
Chan, A. J., Sun, H., Holt, S., and van der Schaar, M · 2024
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Self-play fine-tuning converts weak language models to strong language models
Chen, Z., Deng, Y., Yuan, H., Ji, K., and Gu, Q · 2024
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Kto: Model alignment as prospect theoretic optimization
Ethayarajh, K., Xu, W., Muennighoff, N., Jurafsky, D., and Kiela, D · 2024
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Direct language model alignment from online ai feedback
Guo, S., Zhang, B., Liu, T., Liu, T., Khalman, M., Llinares, F., Rame, A., Mesnard, T., Zhao, Y., Piot, B., et al · 2024
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Rewardbench: Evaluating reward models for language modeling, 2024
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Understanding the performance gap between online and offline alignment algorithms
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Gemma: Open models based on gemini research and technology
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Imitating language via scalable inverse reinforcement learning
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Is dpo superior to ppo for llm alignment? a comprehensive study
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