From the 1 of 11 linked papers with an AI index.
11 papers
DeepSearch-World: Self-Distillation for Deep Search Agents in a Verifiable Environment
Xinyu Geng, Xuanhua He, Sixiang Chen +7
The paper introduces DeepSearch-World, a deterministic, verifiable web environment, and DeepSearch-Evolve, a self‑distillation framework that lets web search agents improve from th…
XSkill: Continual Learning from Experience and Skills in Multimodal Agents
Guanyu Jiang, Zhaochen Su, Xiaoye Qu +1
Multimodal agents can now tackle complex reasoning tasks with diverse tools, yet they still suffer from inefficient tool use and inflexible orchestration in open-ended settings. A…
CostBench: Evaluating Multi-Turn Cost-Optimal Planning and Adaptation in Dynamic Environments for LLM Tool-Use Agents
Jiayu Liu, Cheng Qian, Zhaochen Su +4
Current evaluations of Large Language Model (LLM) agents primarily emphasize task completion, often overlooking resource efficiency and adaptability. This neglects a crucial capabi…
RedAct: Redacting Agent Capability Traces for Procedural Skill Protection
Shuwen Xu, Zhitao He, Yi R. Fung
Users rely on execution traces to observe agent behavior, diagnose failures, and ensure accountability. These traces contain rich procedural detail, including tool invocations, int…
Towards On-Policy Data Evolution for Visual-Native Multimodal Deep Search Agents
Shijue Huang, Hangyu Guo, Guanting Dong +8
Multimodal deep search requires an agent to solve open-world problems by chaining search, tool use, and visual reasoning over evolving textual and visual context. Two bottlenecks l…
Scalable Token-Level Hallucination Detection in Large Language Models
Rui Min, Tianyu Pang, Chao Du +2
Large language models (LLMs) have demonstrated remarkable capabilities, but they still frequently produce hallucinations. These hallucinations are difficult to detect in reasoning-…