2 citations · 7 across the 9 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
cs.CL2025
Benchmarking Foundation Models with Retrieval-Augmented Generation in Olympic-Level Physics Problem Solving
Shunfeng Zheng, Yudi Zhang, Meng Fang +4
Retrieval-augmented generation (RAG) with foundation models has achieved strong performance across diverse tasks, but their capacity for expert-level reasoning-such as solving Olym…
cs.CL2025
Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones?
Yudi Zhang, Lu Wang, Meng Fang +8
Distilling large language models (LLMs) typically involves transferring the teacher model's responses through supervised fine-tuning (SFT). However, this approach neglects the pote…
cs.CL2024★ 2 cited
Large Language Models Are Neurosymbolic Reasoners
Meng Fang, Shilong Deng, Yudi Zhang +4
A wide range of real-world applications is characterized by their symbolic nature, necessitating a strong capability for symbolic reasoning. This paper investigates the potential a…