5 papers
Efficient PRM Training Data Synthesis via Formal Verification
Ryo Kamoi, Yusen Zhang, Nan Zhang +4
Process Reward Models (PRMs) have emerged as a promising approach for improving LLM reasoning capabilities by providing process supervision over reasoning traces. However, existing…
When Reasoning Meets Compression: Understanding the Effects of LLMs Compression on Large Reasoning Models
Nan Zhang, Eugene Kwek, Yusen Zhang +3
Compression methods, including quantization, distillation, and pruning, improve the computational efficiency of large reasoning models (LRMs). However, existing studies either fail…
QuantLRM: Quantization of Large Reasoning Models via Fine-Tuning Signals
Nan Zhang, Eugene Kwek, Yusen Zhang +4
Weight-only quantization is important for compressing Large Language Models (LLMs). Inspired by the spirit of classical magnitude pruning, we study whether the magnitude of weight…
Enhance Multimodal Consistency and Coherence for Text-Image Plan Generation
Xiaoxin Lu, Ranran Haoran Zhang, Yusen Zhang +1
People get informed of a daily task plan through diverse media involving both texts and images. However, most prior research only focuses on LLM's capability of textual plan genera…
Coverage-based Fairness in Multi-document Summarization
Haoyuan Li, Yusen Zhang, Rui Zhang +1
Fairness in multi-document summarization (MDS) measures whether a system can generate a summary fairly representing information from documents with different social attribute value…