3 citations · 3 across the 10 of their papers we have counts for
7 papers · 1 filter
Task-Aware Resolution Optimization for Visual Large Language Models
Weiqing Luo, Zhen Tan, Yifan Li +4
Real-world vision-language applications demand varying levels of perceptual granularity. However, most existing visual large language models (VLLMs), such as LLaVA, pre-assume a fi…
Contact-Aware Amodal Completion for Human-Object Interaction via Multi-Regional Inpainting
Seunggeun Chi, Enna Sachdeva, Pin-Hao Huang +1
Amodal completion, which is the process of inferring the full appearance of objects despite partial occlusions, is crucial for understanding complex human-object interactions (HOI)…
Occlusion-Aware Temporally Consistent Amodal Completion for 3D Human-Object Interaction Reconstruction
Hyungjun Doh, Dong In Lee, Seunggeun Chi +4
We introduce a novel framework for reconstructing dynamic human-object interactions from monocular video that overcomes challenges associated with occlusions and temporal inconsist…
Efficient MAP Estimation of LLM Judgment Performance with Prior Transfer
Huaizhi Qu, Inyoung Choi, Zhen Tan +6
LLM ensembles are widely used for LLM judges. However, how to estimate their accuracy, especially in an efficient way, is unknown. In this paper, we present a principled maximum a…
GFlowVLM: Enhancing Multi-step Reasoning in Vision-Language Models with Generative Flow Networks
Haoqiang Kang, Enna Sachdeva, Piyush Gupta +2
Vision-Language Models (VLMs) have recently shown promising advancements in sequential decision-making tasks through task-specific fine-tuning. However, common fine-tuning methods,…
Can Hallucination Correction Improve Video-Language Alignment?
Lingjun Zhao, Mingyang Xie, Paola Cascante-Bonilla +2
Large Vision-Language Models often generate hallucinated content that is not grounded in its visual inputs. While prior work focuses on mitigating hallucinations, we instead explor…
Generalized Mission Planning for Heterogeneous Multi-Robot Teams via LLM-constructed Hierarchical Trees
Piyush Gupta, David Isele, Enna Sachdeva +4
We present a novel mission-planning strategy for heterogeneous multi-robot teams, taking into account the specific constraints and capabilities of each robot. Our approach employs…