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cs.CL2026
STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?
Hanxiang Chao, Yihan Bai, Rui Sheng +2
Large Language Model (LLM) agents are increasingly expected to maintain coherent, long-term personalized memory, yet current benchmarks primarily measure static fact retrieval, ove…
cs.CL2025★ 1 cited
Search Arena: Analyzing Search-Augmented LLMs
Mihran Miroyan, Tsung-Han Wu, Logan King +8
Search-augmented language models combine web search with Large Language Models (LLMs) to improve response groundedness and freshness. However, analyzing these systems remains chall…
cs.CL2023
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng +10
Studying how people interact with large language models (LLMs) in real-world scenarios is increasingly important due to their widespread use in various applications. In this paper,…