LIONs: An Empirically Optimized Approach to Align Language Models

LIONs: An Empirically Optimized Approach to Align Language Models

9 July 2024

Zhou Yu

Papers citing "LIONs: An Empirically Optimized Approach to Align Language Models"

9 / 9 papers shown

Title
Think2SQL: Reinforce LLM Reasoning Capabilities for Text2SQL Simone Papicchio Simone Rossi Luca Cagliero Paolo Papotti ReLM LMTD AI4TS LRM 60 0 0 21 Apr 2025
FocalPO: Enhancing Preference Optimizing by Focusing on Correct Preference Rankings Tong Liu Xiao Yu Wenxuan Zhou Jindong Gu Volker Tresp 39 0 0 11 Jan 2025
Long Is More for Alignment: A Simple but Tough-to-Beat Baseline for Instruction Fine-Tuning Hao Zhao Maksym Andriushchenko Francesco Croce Nicolas Flammarion ALM 97 44 0 07 Feb 2024
LESS: Selecting Influential Data for Targeted Instruction Tuning Mengzhou Xia Sadhika Malladi Suchin Gururangan Sanjeev Arora Danqi Chen 82 193 0 06 Feb 2024
KTO: Model Alignment as Prospect Theoretic Optimization Kawin Ethayarajh Winnie Xu Niklas Muennighoff Dan Jurafsky Douwe Kiela 182 456 0 02 Feb 2024
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 333 11,953 0 04 Mar 2022
Multitask Prompted Training Enables Zero-Shot Task Generalization Victor Sanh Albert Webson Colin Raffel Stephen H. Bach Lintang Sutawika ... T. Bers Stella Biderman Leo Gao Thomas Wolf Alexander M. Rush LRM 213 1,661 0 15 Oct 2021
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 264 4,489 0 23 Jan 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 292 1,595 0 18 Sep 2019