3 citations · 8 across the 25 of their papers we have counts for
7 papers · 2 filters
Seeing, Maintaining, and Learning: The Evolution of Multimodal Agent Memory
Minghao Guo, Qingyue Jiao, Xiujin Liu +77
Multimodal models and agents have emerged to enable AI systems to learn from and interact with the real world more like humans by integrating information across multiple modalities…
Demystifying Agent Skills: Why They Work-Until They Don't
Zhiyuan Jiang, Fangrui Huang, Hanwen Xing +6
Skills have emerged as a practical and effective approach for enhancing LLM agents at inference time through structured packages of knowledge. However, existing evaluations largely…
Quantifying Consistency in LLM Logical Reasoning via Structural Uncertainty
Baishali Chaudhury, Mengdie Flora Wang, Hyunji Hayley Park +3
Large language models can arrive at the same answer through reasoning paths that are unstable, contradictory, or difficult to rank consistently -- a failure mode especially prevale…
Knowing When to Ask: Self-Gated Clarification for Hierarchical Language Agents
Aijing Gao, Yiming Kang, Mengdie Flora Wang +1
In hierarchical reasoning, failures often originate at intermediate decision points where the agent commits to a wrong branch without recognizing that it lacks critical information…
Avenir-Web: Human-Experience-Imitating Multimodal Web Agents with Mixture of Grounding Experts
Aiden Yiliu Li, Xinyue Hao, Shilong Liu +1
Despite advances in multimodal large language models, autonomous web agents still struggle to reliably execute long-horizon tasks on complex and dynamic web interfaces. Existing ag…
FutureX-Pro: Extending Future Prediction to High-Value Vertical Domains
Jiashuo Liu, Siyuan Chen, Zaiyuan Wang +38
Building upon FutureX, which established a live benchmark for general-purpose future prediction, this report introduces FutureX-Pro, including FutureX-Finance, FutureX-Retail, Futu…
CubeBench: Diagnosing Interactive, Long-Horizon Spatial Reasoning Under Partial Observations
Huan-ang Gao, Zikang Zhang, Tianwei Luo +9
Large Language Model (LLM) agents, while proficient in the digital realm, face a significant gap in physical-world deployment due to the challenge of forming and maintaining a robu…