1 citations · 1 across the 5 of their papers we have counts for
6 papers
OmniTrace: A Unified Framework for Generation-Time Source Attribution in Omni-Modal LLMs
Qianqi Yan, Yichen Guo, Ching-Chen Kuo +4
An omni-modal language model can answer a question about a multimodal document, a recording, or a video, but it cannot show which part of the input the answer came from. Asking the…
SafePro: Evaluating the Safety of Professional-Level AI Agents
Kaiwen Zhou, Shreedhar Jangam, Ashwin Nagarajan +7
Large language model-based agents are rapidly evolving from simple conversational assistants into autonomous systems capable of performing complex, professional-level tasks in vari…
GRIT: Teaching MLLMs to Think with Images
Yue Fan, Xuehai He, Diji Yang +6
Recent studies have demonstrated the efficacy of using Reinforcement Learning (RL) in building reasoning models that articulate chains of thoughts prior to producing final answers.…
Multimodal Inconsistency Reasoning (MMIR): A New Benchmark for Multimodal Reasoning Models
Qianqi Yan, Yue Fan, Hongquan Li +5
Existing Multimodal Large Language Models (MLLMs) are predominantly trained and tested on consistent visual-textual inputs, leaving open the question of whether they can handle inc…
Read Anywhere Pointed: Layout-aware GUI Screen Reading with Tree-of-Lens Grounding
Yue Fan, Lei Ding, Ching-Chen Kuo +6
Graphical User Interfaces (GUIs) are central to our interaction with digital devices and growing efforts have been made to build models for various GUI understanding tasks. However…
Muffin or Chihuahua? Challenging Multimodal Large Language Models with Multipanel VQA
Yue Fan, Jing Gu, Kaiwen Zhou +5
Multipanel images, commonly seen as web screenshots, posters, etc., pervade our daily lives. These images, characterized by their composition of multiple subfigures in distinct lay…