2 citations · 2 across the 4 of their papers we have counts for
5 papers
SHarP: Saliency-based Pruning of Agent Harnesses
Xinyi Gao, Qiucheng Wu, Kaizhi Qian +3
Agent harnesses are systems that coordinate model calls, tool use, and task execution to help large language models complete complex tasks. To meet task requirements and address fa…
Ref-Adv: Exploring MLLM Visual Reasoning in Referring Expression Tasks
Qihua Dong, Kuo Yang, Lin Ju +6
Referring Expression Comprehension (REC) links language to region level visual perception. Standard benchmarks (RefCOCO, RefCOCO+, RefCOCOg) have progressed rapidly with multimodal…
DynaSaur: Large Language Agents Beyond Predefined Actions
Dang Nguyen, Viet Dac Lai, Seunghyun Yoon +9
Existing LLM agent systems typically select actions from a fixed and predefined set at every step. While this approach is effective in closed, narrowly scoped environments, it pres…
VSP: Assessing the dual challenges of perception and reasoning in spatial planning tasks for VLMs
Qiucheng Wu, Handong Zhao, Michael Saxon +4
Vision language models (VLMs) are an exciting emerging class of language models (LMs) that have merged classic LM capabilities with those of image processing systems. However, the…
Fine-tuning CLIP Text Encoders with Two-step Paraphrasing
Hyunjae Kim, Seunghyun Yoon, Trung Bui +4
Contrastive language-image pre-training (CLIP) models have demonstrated considerable success across various vision-language tasks, such as text-to-image retrieval, where the model…