6 papers
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…
Self-Critique Guided Iterative Reasoning for Multi-hop Question Answering
Zheng Chu, Huiming Fan, Jingchang Chen +8
Although large language models (LLMs) have demonstrated remarkable reasoning capabilities, they still face challenges in knowledge-intensive multi-hop reasoning. Recent work explor…
Investigating and Enhancing the Robustness of Large Multimodal Models Against Temporal Inconsistency
Jiafeng Liang, Shixin Jiang, Xuan Dong +7
Large Multimodal Models (LMMs) have recently demonstrated impressive performance on general video comprehension benchmarks. Nevertheless, for broader applications, the robustness o…
From Specific-MLLMs to Omni-MLLMs: A Survey on MLLMs Aligned with Multi-modalities
Shixin Jiang, Jiafeng Liang, Jiyuan Wang +6
To tackle complex tasks in real-world scenarios, more researchers are focusing on Omni-MLLMs, which aim to achieve omni-modal understanding and generation. Beyond the constraints o…