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cs.CL2026
From Similarity to Structure: Training-free LLM Context Compression with Hybrid Graph Priors
Yitian Zhou, Chaoning Zhang, Jiaquan Zhang +6
Long-context large language models remain computationally expensive to run and often fail to reliably process very long inputs, which makes context compression an important compone…
cs.CL2026
Small Language Model Helps Resolve Semantic Ambiguity of LLM Prompt
Zhenzhen Huang, Chaoning Zhang, Fachrina Dewi Puspitasari +4
Large language models (LLMs) are increasingly utilized in various complex reasoning tasks due to their excellent instruction following capability. However, the model's performance…
cs.CL2025
Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement
Liqin Ye, Agam Shah, Chao Zhang +1
The traditional process of creating labeled datasets is labor-intensive and expensive. Recent breakthroughs in open-source large language models (LLMs) have opened up a new avenue…