activity
20212026
most citedZero-Shot Dense Video Captioning by Jointly Optimizing Text and Moment

5 citations · 15 across the 9 of their papers we have counts for

collaborators

10 papers

cs.CV2026

CRAG-MM-Diagnostics: Enabling Stage-Wise Analysis of Knowledge-Intensive VQA

Hanseok Oh, Parishad BehnamGhader, Benno Krojer +4

Knowledge-Intensive Visual Question Answering (KI-VQA) benchmarks evaluate Vision-Language Models (VLMs) as multimodal knowledge assistants by requiring external information beyond…

cs.CL2026

Subject-level Inference for Realistic Text Anonymization Evaluation

Myeong Seok Oh, Dong-Yun Kim, Hanseok Oh +6

Current text anonymization evaluation relies on span-based metrics that fail to capture what an adversary could actually infer, and assumes a single data subject, ignoring multi-su…

cs.CL2025

Instruction Tuning with and without Context: Behavioral Shifts and Downstream Impact

Hyunji Lee, Seunghyun Yoon, Yunjae Won +7

Instruction tuning is a widely used approach to improve the instruction-following ability of large language models (LLMs). Instruction-tuning datasets typically include a mixture o…

cs.CL2024

The BiGGen Bench: A Principled Benchmark for Fine-grained Evaluation of Language Models with Language Models

Seungone Kim, Juyoung Suk, Ji Yong Cho +29

As language models (LMs) become capable of handling a wide range of tasks, their evaluation is becoming as challenging as their development. Most generation benchmarks currently as…

cs.CL2024

INSTRUCTIR: A Benchmark for Instruction Following of Information Retrieval Models

Hanseok Oh, Hyunji Lee, Seonghyeon Ye +4

Despite the critical need to align search targets with users' intention, retrievers often only prioritize query information without delving into the users' intended search context.…

cs.CL2023★ 1 cited

KTRL+F: Knowledge-Augmented In-Document Search

Hanseok Oh, Haebin Shin, Miyoung Ko +2

We introduce a new problem KTRL+F, a knowledge-augmented in-document search task that necessitates real-time identification of all semantic targets within a document with the aware…

cs.CV2023★ 5 cited

Zero-Shot Dense Video Captioning by Jointly Optimizing Text and Moment

Yongrae Jo, Seongyun Lee, Aiden SJ Lee +3

Dense video captioning, a task of localizing meaningful moments and generating relevant captions for videos, often requires a large, expensive corpus of annotated video segments pa…

cs.IR2022★ 4 cited

Nonparametric Decoding for Generative Retrieval

Hyunji Lee, Jaeyoung Kim, Hoyeon Chang +5

The generative retrieval model depends solely on the information encoded in its model parameters without external memory, its information capacity is limited and fixed. To overcome…

cs.IR2022★ 3 cited

Generative Multi-hop Retrieval

Hyunji Lee, Sohee Yang, Hanseok Oh +1

A common practice for text retrieval is to use an encoder to map the documents and the query to a common vector space and perform a nearest neighbor search (NNS); multi-hop retriev…

cs.CV2021★ 2 cited

ViSeRet: A simple yet effective approach to moment retrieval via fine-grained video segmentation

Aiden Seungjoon Lee, Hanseok Oh, Minjoon Seo

Video-text retrieval has many real-world applications such as media analytics, surveillance, and robotics. This paper presents the 1st place solution to the video retrieval track o…