activity
20242026
collaborators

25 papers

cs.CL2026

Food4All: An Agentic Framework and Benchmark for Food Resource Navigation with Adaptive User Understanding

Yiyang Li, Weixiang Sun, Tianyi Ma +3

Food assistance referral requires conversational agents to translate underspecified, often noisy help-seeking dialogues into locally valid resource recommendations. We present Food…

cs.AI2026

Mitigating Misalignment Contagion by Steering with Implicit Traits

Maria Chang, Ronny Luss, Miao Liu +3

Language models (LMs) are increasingly used in high-stakes, multi-agent settings, where following instructions and maintaining value alignment are critical. Most alignment research…

cs.AI2026

Patching LLM Like Software: A Lightweight Method for Improving Safety Policy in Large Language Models

Huzaifa Arif, Keerthiram Murugesan, Ching-Yun Ko +3

We propose patching for large language models (LLMs) like software versions, a lightweight and modular approach for addressing safety vulnerabilities. While vendors release improve…

cs.AI2026

Context Attribution with Multi-Armed Bandit Optimization

Deng Pan, Keerthiram Murugesan, Ting Hua +2

Understanding which parts of the retrieved context contribute to a large language model's generated answer is essential for building interpretable and trustworthy retrieval-augment…

cs.CL2026

OjaKV: Context-Aware Online Low-Rank KV Cache Compression

Yuxuan Zhu, David H. Yang, Mohammad Mohammadi Amiri +3

The expanding long-context capabilities of large language models are constrained by a significant memory bottleneck: the key-value (KV) cache required for autoregressive generation…

cs.LG2026

ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval

David H. Yang, Yuxuan Zhu, Mohammad Mohammadi Amiri +4

Large language models (LLMs) have shown great performance on complex reasoning tasks but often require generating long intermediate thoughts before reaching a final answer. During…