activity
20232026
most citedLarge Language Models are Temporal and Causal Reasoners for Video Question Answering

2 citations · 4 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2026

WearableQA: A Benchmark for Health Reasoning over Real-World Wearable Data

Ji Soo Lee, Xilun Chen, Pierce Chuang +5

Recent advances in wearable sensing enable continuous monitoring of physiological and behavioral signals, yet existing benchmarks rarely evaluate whether AI systems can reason over…

cs.CV2026

Reason in the Words You Speak: Idiolectal Paraphrasing Off-Policy Traces for Reasoning Distillation in VideoLLMs

Ji Soo Lee, Jinyoung Park, Seohyun Lee +4

Recent large language models achieve strong performance on complex reasoning tasks, where reinforcement learning with Group Relative Policy Optimization (GRPO) has emerged as a lea…

cs.CV2025

Captioning for Text-Video Retrieval via Dual-Group Direct Preference Optimization

Ji Soo Lee, Byungoh Ko, Jaewon Cho +3

In text-video retrieval, auxiliary captions are often used to enhance video understanding, bridging the gap between the modalities. While recent advances in multi-modal large langu…

cs.CV2025

Bidirectional Likelihood Estimation with Multi-Modal Large Language Models for Text-Video Retrieval

Dohwan Ko, Ji Soo Lee, Minhyuk Choi +2

Text-Video Retrieval aims to find the most relevant text (or video) candidate given a video (or text) query from large-scale online databases. Recent work leverages multi-modal lar…

cs.CV2025

VidChain: Chain-of-Tasks with Metric-based Direct Preference Optimization for Dense Video Captioning

Ji Soo Lee, Jongha Kim, Jeehye Na +2

Despite the advancements of Video Large Language Models (VideoLLMs) in various tasks, they struggle with fine-grained temporal understanding, such as Dense Video Captioning (DVC).…

cs.CV2023★ 2 cited

Large Language Models are Temporal and Causal Reasoners for Video Question Answering

Dohwan Ko, Ji Soo Lee, Wooyoung Kang +2

Large Language Models (LLMs) have shown remarkable performances on a wide range of natural language understanding and generation tasks. We observe that the LLMs provide effective p…

cs.CV2023★ 2 cited

Open-vocabulary Video Question Answering: A New Benchmark for Evaluating the Generalizability of Video Question Answering Models

Dohwan Ko, Ji Soo Lee, Miso Choi +3

Video Question Answering (VideoQA) is a challenging task that entails complex multi-modal reasoning. In contrast to multiple-choice VideoQA which aims to predict the answer given s…