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20242026
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cs.AI2026

Understanding Reasoning in LLMs through Strategic Information Allocation under Uncertainty

Jeonghye Kim, Xufang Luo, Minbeom Kim +3

LLMs often exhibit Aha moments such as self-correction after tokens like "Wait," yet the underlying mechanism remains unclear. Standard LLMs collapse mainly through silent divergen…

cs.AI2026

ReflectCAP: Detailed Image Captioning with Reflective Memory

Kyungmin Min, Minbeom Kim, Kang-il Lee +2

Detailed image captioning demands both factual grounding and fine-grained coverage, yet existing methods have struggled to achieve them simultaneously. We address this tension with…

cs.AI2025

Program Synthesis via Test-Time Transduction

Kang-il Lee, Jahyun Koo, Seunghyun Yoon +4

We introduce transductive program synthesis, a new formulation of the program synthesis task that explicitly leverages test inputs during synthesis. While prior approaches to progr…

cs.AI2025

Mitigating Hallucinations in Large Vision-Language Models via Summary-Guided Decoding

Kyungmin Min, Minbeom Kim, Kang-il Lee +2

Large Vision-Language Models (LVLMs) demonstrate impressive capabilities in generating detailed and coherent responses from visual inputs. However, they are prone to generate hallu…

cs.AI2025

VLind-Bench: Measuring Language Priors in Large Vision-Language Models

Kang-il Lee, Minbeom Kim, Seunghyun Yoon +4

Large Vision-Language Models (LVLMs) have demonstrated outstanding performance across various multimodal tasks. However, they suffer from a problem known as language prior, where r…