68 citations · 228 across the 46 of their papers we have counts for
29 papers · 1 filter
Let Agents Design How They Search: Automatic Interface Optimization for Agentic Search
Sangjune An, Jaeyoon Jung, Yumin Choi +4
Agentic search depends on the interface through which a language-model agent accesses and explores a corpus. Existing interface designs are fixed by hand and applied unchanged to e…
EvoDuet: Bilevel Co-Evolution of Web Searching and Task Solving for Scientific Discovery
Young-Jun Lee, Jinheon Baek, Soyeong Jeong +5
Evolutionary search with large language models (LLMs) can stall when progress requires external knowledge the model lacks. Supplying relevant documents helps, but simply adding web…
MemRefine: LLM-Guided Compression for Long-Term Agent Memory
Minjae Kim, Jinheon Baek, Soyeong Jeong +1
Large language model (LLM) agents are increasingly expected to operate over long-term interactions, where information from past dialogues must be preserved and recalled to support…
TIDE: Proactive Multi-Problem Discovery via Template-Guided Iteration
Soyeong Jeong, Jinheon Baek, Minki Kang +1
Agents are widely deployed as assistants over documents, tools, and code. However, they typically act only on explicit user requests, which surface only the problems the user has n…
OmniRetrieval: Unified Retrieval across Heterogeneous Knowledge Sources
Jinheon Baek, Soyeong Jeong, Sangwoo Park +5
Real-world information needs require access to structurally diverse knowledge sources, from unstructured text and relational tables to knowledge graphs and property graphs. Existin…
On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists
Seungone Kim, Dongkeun Yoon, Kiril Gashteovski +55
With the advancement of AI capabilities, AI reviewers are beginning to be deployed in scientific peer review, yet their capability and credibility remain in question: many scientis…
Knowledge Base Construction for Knowledge-Augmented Text-to-SQL
Jinheon Baek, Horst Samulowitz, Oktie Hassanzadeh +4
Text-to-SQL aims to translate natural language queries into SQL statements, which is practical as it enables anyone to easily retrieve the desired information from databases. Recen…
CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation
Emilio Villa-Cueva, Sholpan Bolatzhanova, Diana Turmakhan +32
Translating cultural content poses challenges for machine translation systems due to the differences in conceptualizations between cultures, where language alone may fail to convey…
System Prompt Optimization with Meta-Learning
Yumin Choi, Jinheon Baek, Sung Ju Hwang
Large Language Models (LLMs) have shown remarkable capabilities, with optimizing their input prompts playing a pivotal role in maximizing their performance. However, while LLM prom…
UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities
Woongyeong Yeo, Kangsan Kim, Soyeong Jeong +2
Retrieval-Augmented Generation (RAG) has shown substantial promise in improving factual accuracy by grounding model responses with external knowledge relevant to queries. However,…
Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning
Minju Seo, Jinheon Baek, Seongyun Lee +1
Despite the rapid growth of machine learning research, corresponding code implementations are often unavailable, making it slow and labor-intensive for researchers to reproduce res…
Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching
Simon A. Aytes, Jinheon Baek, Sung Ju Hwang
Recent advances in large language models (LLMs) have enabled strong reasoning capabilities through Chain-of-Thought (CoT) prompting, which elicits step-by-step problem solving, but…
Towards Better Understanding of Program-of-Thought Reasoning in Cross-Lingual and Multilingual Environments
Patomporn Payoungkhamdee, Pume Tuchinda, Jinheon Baek +6
Multi-step reasoning is essential for large language models (LLMs), yet multilingual performance remains challenging. While Chain-of-Thought (CoT) prompting improves reasoning, it…
Efficient Real-time Refinement of Language Model Text Generation
Joonho Ko, Jinheon Baek, Sung Ju Hwang
Large language models (LLMs) have shown remarkable performance across a wide range of natural language tasks. However, a critical challenge remains in that they sometimes generate…
Revisiting In-Context Learning with Long Context Language Models
Jinheon Baek, Sun Jae Lee, Prakhar Gupta +3
In-Context Learning (ICL) is a technique by which language models make predictions based on examples provided in their input context. Previously, their context window size imposed…
Unified Multimodal Interleaved Document Representation for Retrieval
Jaewoo Lee, Joonho Ko, Jinheon Baek +2
Information Retrieval (IR) methods aim to identify documents relevant to a query, which have been widely applied in various natural language tasks. However, existing approaches typ…
Database-Augmented Query Representation for Information Retrieval
Soyeong Jeong, Jinheon Baek, Sukmin Cho +2
Information retrieval models that aim to search for documents relevant to a query have shown multiple successes, which have been applied to diverse tasks. Yet, the query from the u…
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…
ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models
Jinheon Baek, Sujay Kumar Jauhar, Silviu Cucerzan +1
The pace of scientific research, vital for improving human life, is complex, slow, and needs specialized expertise. Meanwhile, novel, impactful research often stems from both a dee…
Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity
Soyeong Jeong, Jinheon Baek, Sukmin Cho +2
Retrieval-Augmented Large Language Models (LLMs), which incorporate the non-parametric knowledge from external knowledge bases into LLMs, have emerged as a promising approach to en…
Retrieval-Augmented Data Augmentation for Low-Resource Domain Tasks
Minju Seo, Jinheon Baek, James Thorne +1
Despite large successes of recent language models on diverse tasks, they suffer from severe performance degeneration in low-resource settings with limited training data available.…
Test-Time Self-Adaptive Small Language Models for Question Answering
Soyeong Jeong, Jinheon Baek, Sukmin Cho +2
Recent instruction-finetuned large language models (LMs) have achieved notable performances in various tasks, such as question-answering (QA). However, despite their ability to mem…
Knowledge-Augmented Language Model Verification
Jinheon Baek, Soyeong Jeong, Minki Kang +2
Recent Language Models (LMs) have shown impressive capabilities in generating texts with the knowledge internalized in parameters. Yet, LMs often generate the factually incorrect r…
Phrase Retrieval for Open-Domain Conversational Question Answering with Conversational Dependency Modeling via Contrastive Learning
Soyeong Jeong, Jinheon Baek, Sung Ju Hwang +1
Open-Domain Conversational Question Answering (ODConvQA) aims at answering questions through a multi-turn conversation based on a retriever-reader pipeline, which retrieves passage…