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cs.CL2026

Harness the Memory: A Holistic Evaluation of Memory Substrates in Memory Agents

Wei-Chieh Huang, Weizhi Zhang, Yuchen Wu +12

Memory is becoming core infrastructure for long-horizon LLM agents, yet existing evaluations offer limited guidance on which memory substrate, namely the underlying medium in which…

cs.CL2026

QuantEval: A Benchmark for Financial Quantitative Tasks in Large Language Models

Zhaolu Kang, Junhao Gong, Wenqing Hu +15

Large Language Models (LLMs) have shown strong capabilities across many domains, yet their evaluation in financial quantitative tasks remains fragmented and mostly limited to knowl…

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

Beyond Magic Words: Sharpness-Aware Prompt Evolving for Robust Large Language Models with TARE

Guancheng Wan, Lucheng Fu, Haoxin Liu +10

The performance of Large Language Models (LLMs) hinges on carefully engineered prompts. However, prevailing prompt optimization methods, ranging from heuristic edits and reinforcem…

cs.CL2025

Diagnose, Localize, Align: A Full-Stack Framework for Reliable LLM Multi-Agent Systems under Instruction Conflicts

Guancheng Wan, Leixin Sun, Longxu Dou +10

Large Language Model (LLM)-powered multi-agent systems (MAS) have rapidly advanced collaborative reasoning, tool use, and role-specialized coordination in complex tasks. However, r…