35 citations · 52 across the 10 of their papers we have counts for
10 papers
Benchmarking Visual Feature Representations for LiDAR-Inertial-Visual Odometry Under Challenging Conditions
Eunseon Choi, Junwoo Hong, Daehan Lee +9
Accurate localization in autonomous driving is critical for successful missions including environmental mapping and survivor searches. In visually challenging environments, includi…
Conflict-Aware Soft Prompting for Retrieval-Augmented Generation
Eunseong Choi, June Park, Hyeri Lee +1
Retrieval-augmented generation (RAG) enhances the capabilities of large language models (LLMs) by incorporating external knowledge into their input prompts. However, when the retri…
Multi-view-guided Passage Reranking with Large Language Models
Jeongwoo Na, Jun Kwon, Eunseong Choi +1
Recent advances in large language models (LLMs) have shown impressive performance in passage reranking tasks. Despite their success, LLM-based methods still face challenges in effi…
GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusion
Sunkyung Lee, Minjin Choi, Eunseong Choi +2
Generative recommendation is an emerging paradigm that leverages the extensive knowledge of large language models by formulating recommendations into a text-to-text generation task…
From Reading to Compressing: Exploring the Multi-document Reader for Prompt Compression
Eunseong Choi, Sunkyung Lee, Minjin Choi +2
Large language models (LLMs) have achieved significant performance gains using advanced prompting techniques over various tasks. However, the increasing length of prompts leads to…
Multi-Granularity Guided Fusion-in-Decoder
Eunseong Choi, Hyeri Lee, Jongwuk Lee
In Open-domain Question Answering (ODQA), it is essential to discern relevant contexts as evidence and avoid spurious ones among retrieved results. The model architecture that uses…
Forgetting-aware Linear Bias for Attentive Knowledge Tracing
Yoonjin Im, Eunseong Choi, Heejin Kook +1
Knowledge Tracing (KT) aims to track proficiency based on a question-solving history, allowing us to offer a streamlined curriculum. Recent studies actively utilize attention-based…
ConQueR: Contextualized Query Reduction using Search Logs
Hye-young Kim, Minjin Choi, Sunkyung Lee +3
Query reformulation is a key mechanism to alleviate the linguistic chasm of query in ad-hoc retrieval. Among various solutions, query reduction effectively removes extraneous terms…
SpaDE: Improving Sparse Representations using a Dual Document Encoder for First-stage Retrieval
Eunseong Choi, Sunkyung Lee, Minjin Choi +3
Sparse document representations have been widely used to retrieve relevant documents via exact lexical matching. Owing to the pre-computed inverted index, it supports fast ad-hoc s…
MelBERT: Metaphor Detection via Contextualized Late Interaction using Metaphorical Identification Theories
Minjin Choi, Sunkyung Lee, Eunseong Choi +4
Automated metaphor detection is a challenging task to identify metaphorical expressions of words in a sentence. To tackle this problem, we adopt pre-trained contextualized models,…