collaborators
Showing cs.CLShow all

5 papers · 1 filter

cs.CL2024

SimCT: A Simple Consistency Test Protocol in LLMs Development Lifecycle

Fufangchen Zhao, Guoqiang Jin, Rui Zhao +2

In this work, we report our efforts to advance the standard operation procedure of developing Large Language Models (LLMs) or LLMs-based systems or services in industry. We introdu…

cs.CL2024

Reward Difference Optimization For Sample Reweighting In Offline RLHF

Shiqi Wang, Zhengze Zhang, Rui Zhao +2

With the rapid advances in Large Language Models (LLMs), aligning LLMs with human preferences become increasingly important. Although Reinforcement Learning with Human Feedback (RL…

cs.CL2024

CMR Scaling Law: Predicting Critical Mixture Ratios for Continual Pre-training of Language Models

Jiawei Gu, Zacc Yang, Chuanghao Ding +2

Large Language Models (LLMs) excel in diverse tasks but often underperform in specialized fields due to limited domain-specific or proprietary corpus. Continual pre-training (CPT)…

cs.CL2024

Balancing Speciality and Versatility: A Coarse to Fine Framework for Mitigating Catastrophic Forgetting in Large Language Models

Hengyuan Zhang, Yanru Wu, Dawei Li +4

Aligned Large Language Models (LLMs) showcase remarkable versatility, capable of handling diverse real-world tasks. Meanwhile, aligned LLMs are also expected to exhibit speciality,…

cs.CL2024

Consistency Matters: Explore LLMs Consistency From a Black-Box Perspective

Fufangchen Zhao, Guoqiang Jin, Jiaheng Huang +2

Nowadays both commercial and open-source academic LLM have become the mainstream models of NLP. However, there is still a lack of research on LLM consistency, meaning that througho…