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Shresth Grover

ACL 2026IROS 2026NeurIPS 2026多模态数据与预训练可解释性
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一作贡献30
核心/参与17
方向广度12
合作网络9
1 一作 · 3 篇 · ACL 2026 / IROS 2026 / NeurIPS 2026

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2026 顶会论文

3
作者位次 #3/4ACL 2026Poster· Natural Language Processing

How Do Inpainting Artifacts Propagate to Language?

Pratham Yashwante · Davit Abrahamyan · Shresth Grover · Sukruth Rao

摘要

We study how visual artifacts introduced by diffusion-based inpainting affect language generation in vision-language models. We use a two-stage diagnostic setup in which masked image regions are reconstructed and then provided to captioning models, enabling controlled comparisons between captions...

多模态可解释性数据与预训练OpenReview 项目页
一作IROS 2026Poster· Refining Vision-Language Models for Manipulation

Enhancing Generalization in Vision–Language–Action Models by Preserving Pretrained Representations

Shresth Grover · Akshay Gopalkrishnan · Bo Ai · Henrik Iskov Christensen · Hao Su · Xuanlin Li

可解释性多模态数据与预训练Deep Learning in Grasping and ManipulationRepresentation LearningOpenReview

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