activity
20242026
collaborators

6 papers

cs.CV2026

VGenST-Bench: A Benchmark for Spatio-Temporal Reasoning via Active Video Synthesis

Jinho Park, Youbin Kim, Hogun Park +1

Spatio-temporal reasoning is a core capability for Multimodal Large Language Models (MLLMs) operating in the real world. As such, evaluating it precisely has become an essential ch…

cs.CL2026

EXAONE 4.5 Technical Report

Eunbi Choi, Kibong Choi, Sehyun Chun +55

This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integrating a dedicated visual enc…

cs.LG2026

Characterizing Pattern Matching and Its Limits on Compositional Task Structures

Hoyeon Chang, Jinho Park, Hanseul Cho +7

Despite impressive capabilities, LLMs' successes often rely on pattern-matching behaviors, yet these are also linked to OOD generalization failures in compositional tasks. However,…

cs.CL2025

The CoT Encyclopedia: Analyzing, Predicting, and Controlling how a Reasoning Model will Think

Seongyun Lee, Seungone Kim, Minju Seo +9

Long chain-of-thought (CoT) is an essential ingredient in effective usage of modern large language models, but our understanding of the reasoning strategies underlying these capabi…

cs.CL2024

How language models extrapolate outside the training data: A case study in Textualized Gridworld

Doyoung Kim, Jongwon Lee, Jinho Park +1

Language models' ability to extrapolate learned behaviors to novel, more complex environments beyond their training scope is highly unknown. This study introduces a path planning t…

cs.CL2024

How Do Large Language Models Acquire Factual Knowledge During Pretraining?

Hoyeon Chang, Jinho Park, Seonghyeon Ye +4

Despite the recent observation that large language models (LLMs) can store substantial factual knowledge, there is a limited understanding of the mechanisms of how they acquire fac…