1 citations · 1 across the 3 of their papers we have counts for
5 papers
Bridging the Know-Act Gap via Task-Level Autoregressive Reasoning
Jihyun Janice Ahn, Ryo Kamoi, Berk Atil +34
LLMs often generate seemingly valid answers to flawed or ill-posed inputs. This is not due to missing knowledge: under discriminative prompting, the same models can mostly identify…
Functionality-Oriented LLM Merging on the Fisher--Rao Manifold
Jiayu Wang, Zuojun Ye, Wenpeng Yin
Weight-space merging aims to combine multiple fine-tuned LLMs into a single model without retraining, yet most existing approaches remain fundamentally parameter-space heuristics.…
HRScene: How Far Are VLMs from Effective High-Resolution Image Understanding?
Yusen Zhang, Wenliang Zheng, Aashrith Madasu +14
High-resolution image (HRI) understanding aims to process images with a large number of pixels, such as pathological images and agricultural aerial images, both of which can exceed…
Accelerating Causal Network Discovery of Alzheimer Disease Biomarkers via Scientific Literature-based Retrieval Augmented Generation
Xiaofan Zhou, Liangjie Huang, Pinyang Cheng +4
The causal relationships between biomarkers are essential for disease diagnosis and medical treatment planning. One notable application is Alzheimer's disease (AD) diagnosis, where…
Prompt-Reverse Inconsistency: LLM Self-Inconsistency Beyond Generative Randomness and Prompt Paraphrasing
Jihyun Janice Ahn, Wenpeng Yin
While the inconsistency of LLMs is not a novel topic, prior research has predominantly addressed two types of generative inconsistencies: i) Randomness Inconsistency: running the s…