9 papers
Scaling Self-Evolving Agents via Parametric Memory
Tao Ren, Weiyao Luo, Hui Yang +8
Existing memory-augmented LLM agents store past experience exclusively in prompt space, as textual summaries or retrieved passages, while keeping model parameters frozen throughout…
Perception Without Engagement: Dissecting the Causal Discovery Deficit in LMMs
Jiafeng Liang, Zhihao Zhu, Zihan Zhang +7
Although Large Multimodal Models (LMMs) have achieved strong performance on general video understanding, their susceptibility to textual prior shortcuts during causal discovery has…
The Evolution of Tool Use in LLM Agents: From Single-Tool Call to Multi-Tool Orchestration
Haoyuan Xu, Chang Li, Xinyan Ma +12
Tool use enables large language models (LLMs) to access external information, invoke software systems, and act in digital environments beyond what can be solved from model paramete…
Graph Reasoning Paradigm: Structured and Symbolic Reasoning with Topology-Aware Reinforcement Learning for Large Language Models
Runxuan Liu, Xianhao Ou, Xinyan Ma +13
Long Chain-of-Thought (LCoT), achieved by Reinforcement Learning with Verifiable Rewards (RLVR), has proven effective in enhancing the reasoning capabilities of Large Language Mode…
Analyzing Reasoning Consistency in Large Multimodal Models under Cross-Modal Conflicts
Zhihao Zhu, Jiafeng Liang, Shixin Jiang +5
Large Multimodal Models (LMMs) have demonstrated impressive capabilities in video reasoning via Chain-of-Thought (CoT). However, the robustness of their reasoning chains remains qu…
AI Meets Brain: Memory Systems from Cognitive Neuroscience to Autonomous Agents
Jiafeng Liang, Hao Li, Chang Li +12
Memory serves as the pivotal nexus bridging past and future, providing both humans and AI systems with invaluable concepts and experience to navigate complex tasks. Recent research…