8 papers
ToolTree: Efficient LLM Agent Tool Planning via Dual-Feedback Monte Carlo Tree Search and Bidirectional Pruning
Shuo Yang, Soyeon Caren Han, Yihao Ding +2
Large Language Model (LLM) agents are increasingly applied to complex, multi-step tasks that require interaction with diverse external tools across various domains. However, curren…
BRIDGE: Benchmark for multi-hop Reasoning In long multimodal Documents with Grounded Evidence
Biao Xiang, Soyeon Caren Han, Yihao Ding
Multi-hop question answering (QA) is widely used to evaluate the reasoning capabilities of large language models, yet most benchmarks focus on final answer correctness and overlook…
EvoTool: Self-Evolving Tool-Use Policy Optimization in LLM Agents via Blame-Aware Mutation and Diversity-Aware Selection
Shuo Yang, Soyeon Caren Han, Xueqi Ma +3
LLM-based agents depend on effective tool-use policies to solve complex tasks, yet optimizing these policies remains challenging due to delayed supervision and the difficulty of cr…
When More Is Less: A Systematic Analysis of Spatial and Commonsense Information for Visual Spatial Reasoning
Muku Akasaka, Soyeon Caren Han
Visual spatial reasoning (VSR) remains challenging for modern vision-language models (VLMs), despite advances in multimodal architectures. A common strategy is to inject additional…
Diagnosing Causal Reasoning in Vision-Language Models via Structured Relevance Graphs
Dhita Putri Pratama, Soyeon Caren Han, Yihao Ding
Large Vision-Language Models (LVLMs) achieve strong performance on visual question answering benchmarks, yet often rely on spurious correlations rather than genuine causal reasonin…
Physics-based phenomenological characterization of cross-modal bias in multimodal models
Hyeongmo Kim, Sohyun Kang, Yerin Choi +5
The term 'algorithmic fairness' is used to evaluate whether AI models operate fairly in both comparative (where fairness is understood as formal equality, such as "treat like cases…