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cs.CL2026
Practical Online KV Cache Compaction for LLM Agents: An Empirical Study
Yujian Liu, Jiabao Ji, Li An +4
LLM agents accumulate long trajectories of reasoning steps, tool calls, and environment feedback, making the KV cache a major inference bottleneck. KV cache compaction can reduce t…
cs.CL2026
Modeling Multi-Dimensional Cognitive States in Large Language Models under Cognitive Crowding
Lin Zhong, Siyu Zhu, Zizhen Yuan +5
Modeling human cognitive states is essential for advanced artificial intelligence. Existing Large Language Models (LLMs) mainly address isolated tasks such as emotion analysis or s…
cs.CL2026
T: Progressive Block Scaling for Masked Diffusion Language Models Through Trajectory Aware Reinforcement Learning
Hanchen Xia, Baoyou Chen, Yutang Ge +2
We present T, a simple TraceRL-based training curriculum for progressive block-size scaling in masked diffusion language models (MDMs). Starting from an AR-initialized smal…