2 citations · 4 across the 39 of their papers we have counts for
11 papers · 1 filter
All the Facts, Still the Wrong Answer: Integration Gaps in Vision-Language Models
Yuyang Dai, Yuxia Wang, Zhuohan Xie
Multimodal reasoning requires models to combine multiple pieces of evidence into decisions that satisfy all relevant constraints. Evaluations centered on final-answer accuracy leav…
FinCUABuild: Can Agents Build Reliable Benchmarks for Dynamic Financial Computer Use?
Jingpu Yang, Fengxian Ji, Jinri Guo +7
Financial scenarios are diverse and complex, spanning varying data conditions, tool configurations, and workflows. Yet existing CUA, Computer-Using Agent, evaluation tasks remain l…
Think with Structured Grounding: Perceptual Reinforcement Learning for Chart and Visual-Tabular Understanding
Changjiang Jiang, Qiannian Zhao, Lei Xin +3
Multimodal Large Language Models (MLLMs) capable of thinking with images often rely on external tools for fine-grained perception. However, this reliance introduces significant inf…
Seeing Is Not Deciding: Can Multimodal LLMs Act as Effective CEOs?
Yuyang Dai, Xueqing Peng, Yuxia Wang +2
Large language models are increasingly applied as autonomous decision-making agents. However, in executive business decisions, existing benchmarks are limited to textonly settings.…
LabGuard: Grounding Natural-Language Laboratory Rules into Runtime Guards for Embodied Laboratory Agents
Jingpu Yang, Fengxian Ji, Zhengzhao Lai +8
Scientific embodied agents are increasingly capable of carrying out laboratory procedures, but executing these procedures safely in dynamic laboratory environments remains challeng…
Can LLMs Be CEOs? Benchmarking Strategic Resource Reallocation with Multi-Role Agent Simulation
Yuyang Dai, Xueqing Peng, Lingfei Qian +1
Evaluating the decision-making capabilities of large language models (LLMs) is a growing research priority, yet existing benchmarks focus on isolated cognitive tasks such as reason…
Herculean: An Agentic Benchmark for Financial Intelligence
Xueqing Peng, Zhuohan Xie, Yupeng Cao +60
As AI agents advance, the central question is no longer whether they can solve isolated financial tasks, but whether their capabilities generalize across complete professional work…
The Geometry of Forgetting: Temporal Knowledge Drift as an Independent Axis in LLM Representations
Rania Elbadry, Ahmed Heakl, Fan Zhang +4
Large language models confidently produce outdated answers, and no existing method can detect them. We show this is not an engineering failure but a structural one: temporal drift,…
Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking
Shuzhi Gong, Richard O. Sinnott, Jianzhong Qi +3
Misinformation spreading over the Internet poses a significant threat to both societies and individuals, necessitating robust and scalable fact-checking that relies on retrieving a…
Conv-FinRe: A Conversational and Longitudinal Benchmark for Utility-Grounded Financial Recommendation
Yan Wang, Yi Han, Lingfei Qian +11
Most recommendation benchmarks evaluate how well a model imitates user behavior. In financial advisory, however, observed actions can be noisy or short-sighted under market volatil…
LLM-BabyBench: Can Language Models Plan in Worlds They Can Simulate?
Omar Choukrani, Idriss Malek, Daniil Orel +5
Interactive benchmarks for LLMs usually report a single metric, even though succeeding in them requires models to show several different skills. While those benchmarks are useful f…