9 papers
MATP-BENCH: Can MLLM Be a Good Automated Theorem Prover for Multimodal Problems?
Zhitao He, Zongwei Lyu, Dazhong Chen +2
Numerous theorems, such as those in geometry, are often presented in multimodal forms (e.g., diagrams). Humans benefit from visual reasoning in such settings, using diagrams to gai…
Unveiling the Lack of LVLM Robustness to Fundamental Visual Variations: Why and Path Forward
Zhiyuan Fan, Yumeng Wang, Sandeep Polisetty +1
Large Vision Language Models (LVLMs) excel in various vision-language tasks. Yet, their robustness to visual variations in position, scale, orientation, and context that objects in…
Mathematical Proof as a Litmus Test: Revealing Failure Modes of Advanced Large Reasoning Models
Dadi Guo, Jiayu Liu, Zhiyuan Fan +5
Large reasoning models (e.g., R1, o3) have demonstrated remarkable mathematical problem-solving abilities. However, the high reported accuracy of these advanced models on popular d…
MedEBench: Diagnosing Reliability in Text-Guided Medical Image Editing
Minghao Liu, Zhitao He, Zhiyuan Fan +2
Text-guided image editing has seen significant progress in natural image domains, but its application in medical imaging remains limited and lacks standardized evaluation framework…
TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language Models
Jaewoo Lee, Keyang Xuan, Chanakya Ekbote +3
Multimodal Large Language Models (MLLMs) have shown remarkable versatility in understanding diverse multimodal data and tasks. However, these capabilities come with an increased mo…
Alice: Proactive Learning with Teacher's Demonstrations for Weak-to-Strong Generalization
Shujin Wu, Cheng Qian, Yi R. Fung +2
The growing capabilities of large language models (LLMs) present a key challenge of maintaining effective human oversight. Weak-to-strong generalization (W2SG) offers a promising f…
MimeQA: Towards Socially-Intelligent Nonverbal Foundation Models
Hengzhi Li, Megan Tjandrasuwita, Yi R. Fung +2
As AI becomes more closely integrated with peoples' daily activities, socially intelligent AI that can understand and interact seamlessly with humans in daily lives is increasingly…
VLM2-Bench: A Closer Look at How Well VLMs Implicitly Link Explicit Matching Visual Cues
Jianshu Zhang, Dongyu Yao, Renjie Pi +2
Visually linking matching cues is a crucial ability in daily life, such as identifying the same person in multiple photos based on their cues, even without knowing who they are. De…
Group-Adaptive Threshold Optimization for Robust AI-Generated Text Detection
Minseok Jung, Cynthia Fuertes Panizo, Liam Dugan +4
The advancement of large language models (LLMs) has made it difficult to differentiate human-written text from AI-generated text. Several AI-text detectors have been developed in r…