4 citations · 4 across the 9 of their papers we have counts for
5 papers · 1 filter
Learn from Move: the Next Step for GUI Agents
Jiahao Lu, Yize Shen, Chuanyuan Tan +6
Existing benchmarks for GUI agents primarily focus on increasing task difficulty by extending task horizons. Besides, enabling agents to explore unfamiliar environments and success…
MARCO: Multi-Round Agentic Reinforcement for Conditional Molecular Optimization
Shicheng Fang, Yuxin Wang, Zhuo Yang +6
Molecular optimization is inherently iterative: a candidate is proposed, evaluated against several objectives, and revised while preserving a relationship to the source molecule. M…
What Makes Agent Memory Useful for Reliable Unanswerable Question Handling?
Chuanyuan Tan, Junjie Yu, Yuxin Wang +3
Reliable handling of unanswerable questions (UAQs) is critical for trustworthy LLM-based agents. Although memory is widely used in agent systems, its role in reliable UAQ handling…
AdaptR1: Reinforcement Learning Based Adaptive Interleaved Thinking in Multi-hop Question Answering
Yuxin Wang, Jiahao Lu, Qifeng Wu +5
Large Language Models (LLMs) have achieved remarkable performance in complex reasoning tasks through Chain-of-Thought (CoT) prompting. However, this approach often leads to ``over-…
AgentLongBench: A Controllable Long Benchmark For Long-Contexts Agents via Environment Rollouts
Shicheng Fang, Yuxin Wang, Xiaoran Liu +6
The evolution of Large Language Models (LLMs) into autonomous agents necessitates the management of extensive, dynamic contexts. Current benchmarks, however, remain largely static,…