How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition Paper • 2310.05492 • Published Oct 9, 2023 • 2
ProphetNet: Predicting Future N-gram for Sequence-to-Sequence Pre-training Paper • 2001.04063 • Published Jan 13, 2020
OccuQuest: Mitigating Occupational Bias for Inclusive Large Language Models Paper • 2310.16517 • Published Oct 25, 2023 • 1
Bridging Subword Gaps in Pretrain-Finetune Paradigm for Natural Language Generation Paper • 2106.06125 • Published Jun 11, 2021
PolyLM: An Open Source Polyglot Large Language Model Paper • 2307.06018 • Published Jul 12, 2023 • 25
LLM Critics Help Catch Bugs in Mathematics: Towards a Better Mathematical Verifier with Natural Language Feedback Paper • 2406.14024 • Published Jun 20
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement Paper • 2409.12122 • Published Sep 18 • 3
ProcessBench: Identifying Process Errors in Mathematical Reasoning Paper • 2412.06559 • Published 17 days ago • 68
ProcessBench: Identifying Process Errors in Mathematical Reasoning Paper • 2412.06559 • Published 17 days ago • 68
Aligning Large Language Models via Self-Steering Optimization Paper • 2410.17131 • Published Oct 22 • 21
Aligning Large Language Models via Self-Steering Optimization Paper • 2410.17131 • Published Oct 22 • 21
A Unified View of Delta Parameter Editing in Post-Trained Large-Scale Models Paper • 2410.13841 • Published Oct 17 • 14
Rethinking Data Selection at Scale: Random Selection is Almost All You Need Paper • 2410.09335 • Published Oct 12 • 16