Poster "language model alignment" Papers
31 papers found
Conference
A Common Pitfall of Margin-based Language Model Alignment: Gradient Entanglement
Hui Yuan, Yifan Zeng, Yue Wu et al.
Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux et al.
Explainable Reinforcement Learning from Human Feedback to Improve Alignment
Shicheng Liu, Siyuan Xu, Wenjie Qiu et al.
How to Evaluate Reward Models for RLHF
Evan Frick, Tianle Li, Connor Chen et al.
Interpreting Language Reward Models via Contrastive Explanations
Junqi Jiang, Tom Bewley, Saumitra Mishra et al.
Language Models Learn to Mislead Humans via RLHF
Jiaxin Wen, Ruiqi Zhong, Akbir Khan et al.
Mitigating Reward Over-optimization in Direct Alignment Algorithms with Importance Sampling
Nguyen Phuc, Ngoc-Hieu Nguyen, Duy M. H. Nguyen et al.
Montessori-Instruct: Generate Influential Training Data Tailored for Student Learning
Xiaochuan Li, Zichun Yu, Chenyan Xiong
Preference Distillation via Value based Reinforcement Learning
Minchan Kwon, Junwon Ko, Kangil kim et al.
Quantile Reward Policy Optimization: Alignment with Pointwise Regression and Exact Partition Functions
Simon Matrenok, Skander Moalla, Caglar Gulcehre
Reducing the Probability of Undesirable Outputs in Language Models Using Probabilistic Inference
Stephen Zhao, Aidan Li, Rob Brekelmans et al.
RM-Bench: Benchmarking Reward Models of Language Models with Subtlety and Style
Yantao Liu, Zijun Yao, Rui Min et al.
Scalable Valuation of Human Feedback through Provably Robust Model Alignment
Masahiro Fujisawa, Masaki Adachi, Michael A Osborne
SELF-EVOLVED REWARD LEARNING FOR LLMS
Chenghua Huang, Zhizhen Fan, Lu Wang et al.
SeRA: Self-Reviewing and Alignment of LLMs using Implicit Reward Margins
Jongwoo Ko, Saket Dingliwal, Bhavana Ganesh et al.
SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters
Teng Xiao, Yige Yuan, Zhengyu Chen et al.
Sparta Alignment: Collectively Aligning Multiple Language Models through Combat
Yuru Jiang, Wenxuan Ding, Shangbin Feng et al.
Variational Best-of-N Alignment
Afra Amini, Tim Vieira, Elliott Ash et al.
Vector-ICL: In-context Learning with Continuous Vector Representations
Yufan Zhuang, Chandan Singh, Liyuan Liu et al.
Weak-to-Strong Preference Optimization: Stealing Reward from Weak Aligned Model
Wenhong Zhu, Zhiwei He, Xiaofeng Wang et al.
BRAIn: Bayesian Reward-conditioned Amortized Inference for natural language generation from feedback
Gaurav Pandey, Yatin Nandwani, Tahira Naseem et al.
Controlled Decoding from Language Models
Sidharth Mudgal, Jong Lee, Harish Ganapathy et al.
Degeneration-free Policy Optimization: RL Fine-Tuning for Language Models without Degeneration
Youngsoo Jang, Geon-Hyeong Kim, Byoungjip Kim et al.
Human Alignment of Large Language Models through Online Preference Optimisation
Daniele Calandriello, Zhaohan Guo, REMI MUNOS et al.
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
Banghua Zhu, Michael Jordan, Jiantao Jiao
Linear Alignment: A Closed-form Solution for Aligning Human Preferences without Tuning and Feedback
songyang gao, Qiming Ge, Wei Shen et al.
MaxMin-RLHF: Alignment with Diverse Human Preferences
Souradip Chakraborty, Jiahao Qiu, Hui Yuan et al.
ODIN: Disentangled Reward Mitigates Hacking in RLHF
Lichang Chen, Chen Zhu, Jiuhai Chen et al.
Provably Robust DPO: Aligning Language Models with Noisy Feedback
Sayak Ray Chowdhury, Anush Kini, Nagarajan Natarajan
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
Zixiang Chen, Yihe Deng, Huizhuo Yuan et al.
Towards Efficient Exact Optimization of Language Model Alignment
Haozhe Ji, Cheng Lu, Yilin Niu et al.