activity
20222026
most citedA Gradient Accumulation Method for Dense Retriever under Memory Constraint

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CR2026

AlienLM: Alienization of Language for API-Boundary Privacy in Black-Box LLMs

Jaehee Kim, Pilsung Kang

Modern LLMs are increasingly accessed via black-box APIs, requiring users to transmit sensitive prompts, outputs, and fine-tuning data to external providers, creating a critical pr…

cs.IR2024★ 1 cited

A Gradient Accumulation Method for Dense Retriever under Memory Constraint

Jaehee Kim, Yukyung Lee, Pilsung Kang

InfoNCE loss is commonly used to train dense retriever in information retrieval tasks. It is well known that a large batch is essential to stable and effective training with InfoNC…

cs.CL2024

CheckEval: A reliable LLM-as-a-Judge framework for evaluating text generation using checklists

Yukyung Lee, Joonghoon Kim, Jaehee Kim +4

Existing LLM-as-a-Judge approaches for evaluating text generation suffer from rating inconsistencies, with low agreement and high rating variance across different evaluator models.…

cs.CL2023

Boosting Prompt-Based Self-Training With Mapping-Free Automatic Verbalizer for Multi-Class Classification

Yookyung Kho, Jaehee Kim, Pilsung Kang

Recently, prompt-based fine-tuning has garnered considerable interest as a core technique for few-shot text classification task. This approach reformulates the fine-tuning objectiv…

cs.AI2023

Painsight: An Extendable Opinion Mining Framework for Detecting Pain Points Based on Online Customer Reviews

Yukyung Lee, Jaehee Kim, Doyoon Kim +3

As the e-commerce market continues to expand and online transactions proliferate, customer reviews have emerged as a critical element in shaping the purchasing decisions of prospec…

cs.CV2022

REVECA -- Rich Encoder-decoder framework for Video Event CAptioner

Jaehyuk Heo, YongGi Jeong, Sunwoo Kim +2

We describe an approach used in the Generic Boundary Event Captioning challenge at the Long-Form Video Understanding Workshop held at CVPR 2022. We designed a Rich Encoder-decoder…