The Wisdom of Hindsight Makes Language Models Better Instruction
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The Wisdom of Hindsight Makes Language Models Better Instruction Followers

10 February 2023

Tianjun Zhang

Pieter Abbeel

Joseph E. Gonzalez

Papers citing "The Wisdom of Hindsight Makes Language Models Better Instruction Followers"

16 / 16 papers shown

Title
E2CL: Exploration-based Error Correction Learning for Embodied Agents Hanlin Wang Chak Tou Leong Jian Wang Wenjie Li 32 1 0 05 Sep 2024
On the Transformations across Reward Model, Parameter Update, and In-Context Prompt Deng Cai Huayang Li Tingchen Fu Siheng Li Weiwen Xu ... Leyang Cui Yan Wang Lemao Liu Taro Watanabe Shuming Shi KELM 26 2 0 24 Jun 2024
Generalizing Reward Modeling for Out-of-Distribution Preference Learning Chen Jia 32 2 0 22 Feb 2024
Learning from Mistakes: Iterative Prompt Relabeling for Text-to-Image Diffusion Model Training Xinyan Chen Jiaxin Ge Tianjun Zhang Jiaming Liu Shanghang Zhang VLM EGVM 27 0 0 23 Dec 2023
Reasons to Reject? Aligning Language Models with Judgments Weiwen Xu Deng Cai Zhisong Zhang Wai Lam Shuming Shi ALM 16 14 0 22 Dec 2023
Reinforcement Learning in the Era of LLMs: What is Essential? What is needed? An RL Perspective on RLHF, Prompting, and Beyond Hao Sun OffRL 29 21 0 09 Oct 2023
Cognitive Architectures for Language Agents T. Sumers Shunyu Yao Karthik Narasimhan Thomas L. Griffiths LLMAG LM&Ro 36 151 0 05 Sep 2023
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 293 4,077 0 24 May 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 303 11,909 0 04 Mar 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 315 8,448 0 28 Jan 2022
P-Tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Universally Across Scales and Tasks Xiao Liu Kaixuan Ji Yicheng Fu Weng Lam Tam Zhengxiao Du Zhilin Yang Jie Tang VLM 236 805 0 14 Oct 2021
The Power of Scale for Parameter-Efficient Prompt Tuning Brian Lester Rami Al-Rfou Noah Constant VPVLM 280 3,843 0 18 Apr 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 241 1,916 0 31 Dec 2020
Fine-Tuning Language Models from Human Preferences Daniel M. Ziegler Nisan Stiennon Jeff Wu Tom B. Brown Alec Radford Dario Amodei Paul Christiano G. Irving ALM 275 1,587 0 18 Sep 2019
Improving a Neural Semantic Parser by Counterfactual Learning from Human Bandit Feedback Carolin (Haas) Lawrence Stefan Riezler OffRL 171 56 0 03 May 2018
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 294 6,943 0 20 Apr 2018