5 citations · 5 across the 11 of their papers we have counts for
5 papers · 1 filter
START: Spatial and Textual Learning for Chart Understanding
Zhuoming Liu, Xiaofeng Gao, Feiyang Niu +3
Chart understanding is crucial for deploying multimodal large language models (MLLMs) in real-world scenarios such as analyzing scientific papers and technical reports. Unlike natu…
VaPR -- Vision-language Preference alignment for Reasoning
Rohan Wadhawan, Fabrice Y Harel-Canada, Zi-Yi Dou +3
Preference finetuning methods like Direct Preference Optimization (DPO) with AI-generated feedback have shown promise in aligning Large Vision-Language Models (LVLMs) with human pr…
MDSEval: A Meta-Evaluation Benchmark for Multimodal Dialogue Summarization
Yinhong Liu, Jianfeng He, Hang Su +6
Multimodal Dialogue Summarization (MDS) is a critical task with wide-ranging applications. To support the development of effective MDS models, robust automatic evaluation methods a…
TemMed-Bench: Evaluating Temporal Medical Image Reasoning in Vision-Language Models
Junyi Zhang, Jia-Chen Gu, Wenbo Hu +3
Existing medical reasoning benchmarks for vision-language models primarily focus on analyzing a patient's condition based on an image from a single visit. However, this setting dev…
InSTA: Towards Internet-Scale Training For Agents
Brandon Trabucco, Gunnar Sigurdsson, Robinson Piramuthu +1
The predominant approach for training web navigation agents is to gather human demonstrations for a set of popular websites and hand-written tasks, but it is becoming clear that hu…