From the 1 of 38 linked papers with an AI index.
1 citations · 1 across the 13 of their papers we have counts for
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MultivationBench: A Benchmark for Multimodal Sequential Motivation Reasoning
Kawai Chung, Chunkit Chan, Yauwai Yim +12
The paper introduces MultivationBench, a benchmark that tests multimodal large language models on their ability to reason about evolving human motivations across sequential visual…
Rethinking Prospect Theory for LLMs: Revealing the Instability of Decision-Making under Epistemic Uncertainty
Rui Wang, Qihan Lin, Jiayu Liu +7
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…
NewtonBench: Benchmarking Generalizable Scientific Law Discovery in LLM Agents
Tianshi Zheng, Kelvin Kiu-Wai Tam, Newt Hue-Nam K. Nguyen +10
Large language models are emerging as powerful tools for scientific law discovery, a foundational challenge in AI-driven science. However, existing benchmarks for this task suffer…
DeepPlanner: Scaling Planning Capability for Deep Research Agents via Advantage Shaping
Wei Fan, Wenlin Yao, Zheng Li +6
Large language models (LLMs) augmented with multi-step reasoning and action generation abilities have shown promise in leveraging external tools to tackle complex tasks that requir…
The Cognitive Bandwidth Bottleneck: Shifting Long-Horizon Agent from Planning with Actions to Planning with Schemas
Baixuan Xu, Tianshi Zheng, Zhaowei Wang +4
Enabling LLMs to effectively operate long-horizon task which requires long-term planning and multiple interactions is essential for open-world autonomy. Conventional methods adopt…
Patterns Over Principles: The Fragility of Inductive Reasoning in LLMs under Noisy Observations
Chunyang Li, Weiqi Wang, Tianshi Zheng +1
Inductive reasoning, a cornerstone of human cognition, enables generalization from limited data but hasn't yet been fully achieved by large language models (LLMs). While modern LLM…