13 papers
Meta-Video: Efficient Standardized Evaluation for Video Understanding
Soumya Shamarao Jahagirdar, Anna Kukleva, Vishaal Udandarao +5
Video understanding benchmarks are the primary yardstick for measuring progress in video-language modeling, and a growing body of work relies on them to claim improvements. The rep…
ChartRevise: A Dataset and Evaluation Protocol for Exact Chart Editing via Code
Jiaxiang Tang, Yi Zhou, Chad DeLuca +5
Chart editing requires cross-modal edit grounding, realizing a requested visual change in the code that draws it, with necessary related updates and without altering unrelated cont…
EpiCon: Collective Agent Learning through Co-Evolving Multimodal Memory
Ziyun Zeng, Hang Hua, Shaden Alshammari +3
Agents can learn from past executions, but enabling different agents to reuse and build on one another's experience remains challenging. We introduce EpiCon, a shared multimodal me…
DocHop: Benchmarking Out-of-domain Multi-hop Reasoning in Information-Dense Documents
Zhuoran Yu, Le Thien Phuc Nguyen, Jaden Park +5
Multimodal Large Language Models (MLLMs) have achieved strong performance on structured visual understanding tasks such as chart and document question answering. However, existing…
Aligning Quantum Operators with Large Language Models
Rogerio Feris, Yunchao Liu, Pengyuan Li +2
Can Large Language Models (LLMs) understand and reason about quantum operators? Despite their remarkable capabilities in mathematics and symbolic reasoning, LLMs remain inherently…
Dr. DocBench: A Comprehensive Benchmark for Expert-Level and Difficult Document Parsing
Minglai Yang, Xinyan Velocity Yu, Pengyuan Li +22
Document parsing and recognition are fundamental capabilities for vision-language models (VLMs) and document processing systems. However, existing Optical Character Recognition (OC…
MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents
Ziyun Zeng, Hang Hua, Bocheng Zou +3
Recent GUI agents have made substantial progress in visual grounding and action prediction, yet they remain brittle in long-horizon tasks that require maintaining task state across…
AVRT: Audio-Visual Reasoning Transfer through Single-Modality Teachers
Edson Araujo, Saurabhchand Bhati, M. Jehanzeb Mirza +5
Recent advances in reasoning models have shown remarkable progress in text-based domains, but transferring those capabilities to multimodal settings, e.g., to allow reasoning over…
ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding
Jovana Kondic, Pengyuan Li, Dhiraj Joshi +24
Understanding charts requires models to jointly reason over geometric visual patterns, structured numerical data, and natural language -- a capability where current vision-language…
TTA-Vid: Generalized Test-Time Adaptation for Video Reasoning
Soumya Shamarao Jahagirdar, Edson Araujo, Anna Kukleva +7
Recent video reasoning models have shown strong results on temporal and multimodal understanding, yet they depend on large-scale supervised data and multi-stage training pipelines,…
DAVE: A VLM Vision Encoder for Document Understanding and Web Agents
Brandon Huang, Hang Hua, Zhuoran Yu +3
While Vision-language models (VLMs) have demonstrated remarkable performance across multi-modal tasks, their choice of vision encoders presents a fundamental weakness: their low-le…
Video-R4: Reinforcing Text-Rich Video Reasoning with Visual Rumination
Yolo Y. Tang, Daiki Shimada, Hang Hua +4
Understanding text-rich videos requires reading small, transient textual cues that often demand repeated inspection. Yet most video QA models rely on single-pass perception over fi…
Composition-Grounded Data Synthesis for Visual Reasoning
Xinyi Gu, Jiayuan Mao, Zhang-Wei Hong +5
Pretrained multi-modal large language models (MLLMs) demonstrate strong performance on diverse multimodal tasks, but remain limited in reasoning capabilities for domains where anno…