…combining Thread-Constrained Directed Acyclic Graph and Discourse-Aware Rotary Position Embedding addresses limitations in conversational sentiment analysis by capturing dialogue structure and temporal sequences more effectively. AI-generated summary Conversational Aspect…
…AI-generated summary Long-term agent memory is increasingly multimodal, yet existing evaluations rarely test whether agents preserve the visual evidence needed for later reasoning. In prior work, many visually grounded questions…
…For direct interaction, acting on uncertainty means communicating it honestly; for agentic systems, it becomes the control layer governing when to search and what to trust. Metacognition is thus essential for LLMs…
…checkout this Space You can directly ask Librarian Bot for paper recommendations by tagging it in a comment: @ librarian-bot recommend Get this paper in your agent: hf papers read 2605.02178…
…Jingjie Ning , , , , Abstract Auto research operates as an empirical loop where agents iteratively refine code based on evaluation feedback, achieving improved performance across multiple tasks without human intervention. AI-generated summary We…
…Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management (2026) DataMaster: Data-Centric Autonomous AI Research (2026) MARS$^2$: Scaling Multi-Agent Tree Search via Reinforcement Learning for Code…
…a multi-agent forecasting framework that decomposes time series prediction into specialized stages, enabling effective integration of numerical patterns and contextual information for improved forecasting accuracy and explainability. AI-generated summary Time…
…When Memory Poisoning Looks Like Model Failure in Agentic AI Systems (2026) Done, But Not Sure: Disentangling World Completion from Self-Termination in Embodied Agents (2026) PEAM: Parametric Embodied Agent Memory through…
…AI-generated summary Memory systems are critical for role-playing agents (RPAs) to maintain long-horizon consistency. However, existing RPA memory methods (e.g., profiling) mainly rely on recurrent summarization , whose compression…
…AI-generated summary Distributed blackbox consensus optimization is a fundamental problem in multi-agent systems, where agents must improve a global objective using only local objective queries and limited neighbor communication. Existing…