10 citations · 15 across the 6 of their papers we have counts for
6 papers
ROSE: Benchmarking the Perception-to-Action Gap in Multimodal Models
Yihao Wang, Zijian He, Jie Ren +1
Multimodal large language models (MLLMs) are increasingly expected to act on visual information, yet the same scene may require different actions under different task contexts. How…
Beyond Pixels: Introspective and Interactive Grounding for Visualization Agents
Yiyang Lu, Woong Shin, Ahmad Maroof Karimi +3
Vision-Language Models (VLMs) frequently misread values, hallucinate details, and confuse overlapping elements in charts. Current approaches rely solely on pixel interpretation, cr…
SETS: Leveraging Self-Verification and Self-Correction for Improved Test-Time Scaling
Jiefeng Chen, Jie Ren, Xinyun Chen +4
Recent advancements in Large Language Models (LLMs) have created new opportunities to enhance performance on complex reasoning tasks by leveraging test-time computation. However, e…
MLDT: Multi-Level Decomposition for Complex Long-Horizon Robotic Task Planning with Open-Source Large Language Model
Yike Wu, Jiatao Zhang, Nan Hu +5
In the realm of data-driven AI technology, the application of open-source large language models (LLMs) in robotic task planning represents a significant milestone. Recent robotic t…
Self-Evaluation Improves Selective Generation in Large Language Models
Jie Ren, Yao Zhao, Tu Vu +2
Safe deployment of large language models (LLMs) may benefit from a reliable method for assessing their generated content to determine when to abstain or to selectively generate. Wh…
Universal Self-Consistency for Large Language Model Generation
Xinyun Chen, Renat Aksitov, Uri Alon +7
Self-consistency with chain-of-thought prompting (CoT) has demonstrated remarkable performance gains on various challenging tasks, by utilizing multiple reasoning paths sampled fro…