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20242026
most citedChatCell: Facilitating Single-Cell Analysis with Natural Language

2 citations · 4 across the 13 of their papers we have counts for

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11 papers · 1 filter

cs.CL2026

EM^2Mem: Event-Centric Multimodal Memory for Large Language Models

Yijun Chen, Yaqi Zheng, Yanya Li +11

Multimodal memory offers a scalable interface for long-video question answering, but existing methods often retrieve captions, frames, transcripts, summaries, or graph facts as iso…

cs.CL2026

TokenPilot: Cache-Efficient Context Management for LLM Agents

Buqiang Xu, Zirui Xue, Dianmou Chen +12

As LLM agents are deployed in long-horizon sessions, context accumulation drives up inference costs. Existing approaches utilize text pruning or dynamic memory eviction to minimize…

cs.CL2026

Rethinking Memory as Continuously Evolving Connectivity

Jizhan Fang, Buqiang Xu, Zhixian Wang +12

Existing memory-augmented LLM agents often treat memory as a static repository with pre-defined representations and fixed retrieval pipelines, which is brittle in dynamic agentic e…

cs.CL2026

MemTrace: Tracing and Attributing Errors in Large Language Model Memory Systems

Xinle Deng, Ruobin Zhong, Hujin Peng +15

Memory is essential for enabling large language models to support long-horizon reasoning, yet existing memory systems remain unreliable and difficult to debug. Tracing memory's dyn…

cs.CL2026

Temp-R1: A Unified Autonomous Agent for Complex Temporal KGQA via Reverse Curriculum Reinforcement Learning

Zhaoyan Gong, Zhiqiang Liu, Songze Li +7

Temporal Knowledge Graph Question Answering (TKGQA) is inherently challenging, as it requires sophisticated reasoning over dynamic facts with multi-hop dependencies and complex tem…

cs.CL2026

Illusions of Confidence? Diagnosing LLM Truthfulness via Neighborhood Consistency

Haoming Xu, Ningyuan Zhao, Yunzhi Yao +7

As Large Language Models (LLMs) are increasingly deployed in real-world settings, correctness alone is insufficient. Reliable deployment requires maintaining truthful beliefs under…