13 papers
SimpleSearch-VL: A Simple Recipe for Multimodal Agentic Deep Search
Ming Dai, Zhihong Lu, Jinjie Gu +5
We present SimpleSearch-VL, an efficient, reliable, and practical framework for multimodal agentic search. Its core idea is to improve the agent's own search-and-verification proce…
LiveAgentBench: Comprehensive Benchmarking of Agentic Systems Across 104 Real-World Challenges
Hao Li, Huan Wang, Jinjie Gu +3
As large language models grow more capable, general AI agents have become increasingly prevalent in practical applications. However, existing benchmarks face significant limitation…
Don't Just Fine-tune the Agent, Tune the Environment
Siyuan Lu, Zechuan Wang, Hongxuan Zhang +5
Large Language Model (LLM) agents show great promise for complex, multi-turn tool-use tasks, but their development is often hampered by the extreme scarcity of high-quality trainin…
V2P: Visual Attention Calibration for GUI Grounding via Background Suppression and Center Peaking
Jikai Chen, Long Chen, Dong Wang +6
Precise localization of GUI elements is crucial for the development of GUI agents. Traditional methods rely on bounding box or center-point regression, neglecting spatial interacti…
V2P: Visual Attention Calibration for GUI Grounding via Background Suppression and Center Peaking
Jikai Chen, Long Chen, Dong Wang +6
Precise localization of GUI elements is crucial for the development of GUI agents. Traditional methods rely on bounding box or center-point regression, neglecting spatial interacti…
RAG-R1: Incentivizing the Search and Reasoning Capabilities of LLMs through Multi-query Parallelism
Zhiwen Tan, Jiaming Huang, Qintong Wu +3
Large Language Models (LLMs), despite their remarkable capabilities, are prone to generating hallucinated or outdated content due to their static internal knowledge. While Retrieva…