3 citations · 4 across the 10 of their papers we have counts for
Showing 2026Show all
3 papers · 1 filter
cs.AI2026
From Context to Skills: Can Language Models Learn from Context Skillfully?
Shuzheng Si, Haozhe Zhao, Yu Lei +10
Many real-world tasks require language models (LMs) to reason over complex contexts that exceed their parametric knowledge. This calls for context learning, where LMs directly lear…
cs.CL2026
InFi-Check: Interpretable and Fine-Grained Fact-Checking of LLMs
Yuzhuo Bai, Shuzheng Si, Kangyang Luo +5
Large language models (LLMs) often hallucinate, yet most existing fact-checking methods treat factuality evaluation as a binary classification problem, offering limited interpretab…
cs.CL2026
From Context to EDUs: Faithful and Structured Context Compression via Elementary Discourse Unit Decomposition
Yiqing Zhou, Yu Lei, Shuzheng Si +7
Managing extensive context remains a critical bottleneck for Large Language Models (LLMs), particularly in applications like long-document question answering and autonomous agents…