4 papers
ESPO: Error-Structured Prompt Optimization via Diagnose, Diversify, and Stabilize
Lihao Liu, Peng Tang, Kunwar Yashraj Singh +1
Evolutionary prompt optimizers such as GEPA suffer from prompt bloat: each iteration appends rules and caveats, producing prompts up to 3 longer yet no more accurate. We tr…
R-VLM: Region-Aware Vision Language Model for Precise GUI Grounding
Joonhyung Park, Peng Tang, Sagnik Das +4
Visual agent models for automating human activities on Graphical User Interfaces (GUIs) have emerged as a promising research direction, driven by advances in large Vision Language…
Synthesize Step-by-Step: Tools, Templates and LLMs as Data Generators for Reasoning-Based Chart VQA
Zhuowan Li, Bhavan Jasani, Peng Tang +1
Understanding data visualizations like charts and plots requires reasoning about both visual elements and numerics. Although strong in extractive questions, current chart visual qu…
Enhancing Vision-Language Pre-training with Rich Supervisions
Yuan Gao, Kunyu Shi, Pengkai Zhu +7
We propose Strongly Supervised pre-training with ScreenShots (S4) - a novel pre-training paradigm for Vision-Language Models using data from large-scale web screenshot rendering. U…