10 papers
Citation-Closure Retrieval and Per-Rule Attribution for Real-World Regulatory Compliance Question Answering
Yeong-Joon Ju, Seong-Whan Lee
Deploying Large Language Models (LLMs) for regulatory compliance demands rigorous traceability via comprehensive citations across multi-tiered authority structures. Unlike traditio…
Localizing Input Uncertainty Quantification for Large Language Models via Shapley Values
Seongjun Lee, Suwan Yoon, Changhee Lee
As large language models (LLMs) are increasingly integrated into high-stakes decision-making, the ability to reliably quantify uncertainty has become a critical requirement for saf…
DQE-CIR: Distinctive Query Embeddings through Learnable Attribute Weights and Target Relative Negative Sampling in Composed Image Retrieval
Geon Park, Ji-Hoon Park, Seong-Whan Lee
Composed image retrieval (CIR) addresses the task of retrieving a target image by jointly interpreting a reference image and a modification text that specifies the intended change.…
From Generator to Embedder: Harnessing Innate Abilities of Multimodal LLMs via Building Zero-Shot Discriminative Embedding Model
Yeong-Joon Ju, Seong-Whan Lee
Adapting generative Multimodal Large Language Models (MLLMs) into universal embedding models typically demands resource-intensive contrastive pre-training, while traditional hard n…
Multi-stage Prompt Refinement for Mitigating Hallucinations in Large Language Models
Jung-Woo Shim, Yeong-Joon Ju, Ji-Hoon Park +1
Recent advancements in large language models (LLMs) have shown strong performance in natural language understanding and generation tasks. However, LLMs continue to encounter challe…
CPR: Mitigating Large Language Model Hallucinations with Curative Prompt Refinement
Jung-Woo Shim, Yeong-Joon Ju, Ji-Hoon Park +1
Recent advancements in large language models (LLMs) highlight their fluency in generating responses to diverse prompts. However, these models sometimes generate plausible yet incor…