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cs.CL2026

Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents

Eric Hanchen Jiang, Zhi Zhang, Yuchen Wu +11

Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks. Yet nearly all existing approaches, from graph-structured memo…

cs.CL2026

Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language Models

Hengyuan Zhang, Zhihao Zhang, Mingyang Wang +26

Mechanistic Interpretability (MI) has emerged as a vital approach to demystify the opaque decision-making of Large Language Models (LLMs). However, existing reviews primarily treat…

cs.CL2025

AFM: An Adaptive Agent Foundation Model for Tool-Aware Hybrid Reasoning

Qianben Chen, Jingyi Cao, Jiayu Zhang +12

Large language models split into two families: reasoning-centric LLMs, which strengthen internal chain-of-thought reasoning but cannot invoke external tools, and agentic LLMs, whic…

cs.CL2025

Dynamic Generation of Multi-LLM Agents Communication Topologies with Graph Diffusion Models

Eric Hanchen Jiang, Mengting Li, Guancheng Wan +8

The efficiency of multi-agent systems driven by large language models (LLMs) largely hinges on their communication topology. However, designing an optimal topology is a non-trivial…

cs.CL2025

Sequential Diffusion Language Models

Yangzhou Liu, Yue Cao, Hao Li +13

Diffusion language models (DLMs) have strong theoretical efficiency but are limited by fixed-length decoding and incompatibility with key-value (KV) caches. Block diffusion mitigat…