1 citations · 2 across the 4 of their papers we have counts for
Showing cs.CLShow all
3 papers · 1 filter
cs.CL2025
S2J: Bridging the Gap Between Solving and Judging Ability in Generative Reward Models
Shaoning Sun, Jiachen Yu, Zongqi Wang +3
With the rapid development of large language models (LLMs), generative reward models (GRMs) have been widely adopted for reward modeling and evaluation. Previous studies have prima…
cs.CL2025★ 1 cited
Invisible Entropy: Towards Safe and Efficient Low-Entropy LLM Watermarking
Tianle Gu, Zongqi Wang, Kexin Huang +4
Logit-based LLM watermarking traces and verifies AI-generated content by maintaining green and red token lists and increasing the likelihood of green tokens during generation. Howe…
cs.CL2025
SCAN: Structured Capability Assessment and Navigation for LLMs
Zongqi Wang, Tianle Gu, Chen Gong +3
Evaluating Large Language Models (LLMs) has become increasingly important, with automatic evaluation benchmarks gaining prominence as alternatives to human evaluation. While existi…