Large language model agents can invoke tools fluently, but enterprise workflows demand more than selecting the right tools: actions must strictly comply with organizational policies, tool feedback often conceals hidden side effects under partial observability, and long-horizon tasks require persistent state tracking ac...
Real-world decision-making often involves uncertainty expressed in linguistic rather than numerical terms, and Prospect Theory (PT) provides a classic framework for modeling human behavior under such uncertainty. Although recent studies have developed frameworks to estimate PT parameters for Large Language Models (LLMs...
Rui Wang, Qi-Han Lin, Jiayu Liu et al.· 2 citations
A cross-modal grounding study shows that text-level VCI ordering largely survives faithful rendering and blind image-level preference judgment, supporting Ekphrasis as a measure of visual ideation beyond prose quality.
Hongyu Luo, Hexi Wang, Hui-Hao Jing et al.· 0 citations
AgentIdeaBench is introduced, a multidisciplinary benchmark that evaluates scientific ideation under two matched settings, static observation and active exploration, and Scientific World Modeling is explored, a generation-time loop that refines a draft hypothesis through structured thought experiments.
Yunxiang Mo, Tianshi ZHENG, Yi-Sen Gao et al.· 0 citations
Consistent gains over DVD on LVBench, Video-MME, EgoSchema, and LongVideoBench suggest that option-aware evidence acquisition transfers beyond MMR-V, and proposes PACE (Progressive Acquisition of Critical Evidence), a factor-guided framework for long-video evidence acquisition.
Bai-Xuan Xu, Yinyui Xu, Tianshi ZHENG et al.· 1 citation
Results indicate that MultivationBench presents a significant challenge: all tested models struggle to maintain consistent motivation reasoning across sequential contexts, revealing a critical disconnect between static recognition capabilities and the dynamic reasoning essential for human-like social understanding.
This survey focuses on co-evolution in agentic systems, a multi-component form of self-evolution in which multiple agents and their environment impose adaptive pressure on one another.
Qing Zong, Jiayu Liu, Junhao Shen et al.· 0 citations
This work proposes InferenceDynamics, a flexible and scalable multi-dimensional routing framework by modeling the capability and knowledge of models, and demonstrates its effectiveness and generalizability in group-level routing using modern benchmarks including MMLU-Pro, GPQA, BigGen-Bench, and LiveBench.
Haochen Shi, Tianshi ZHENG, Weiqi Wang et al.· Annual Meeting of the Associ...· 0 citations
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