activity
20162026
most citedAttack of the Tails: Yes, You Really Can Backdoor Federated Learning

110 citations · 197 across the 33 of their papers we have counts for

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Showing 2025Show all

8 papers · 1 filter

cs.LG2025

How to Correctly Report LLM-as-a-Judge Evaluations

Chungpa Lee, Thomas Zeng, Jongwon Jeong +2

Large language models (LLMs) are widely used as scalable evaluators of model responses in lieu of human annotators. However, imperfect sensitivity and specificity of the LLM judges…

cs.LG2025

Soft Task-Aware Routing of Experts for Equivariant Representation Learning

Jaebyeong Jeon, Hyeonseo Jang, Jy-yong Sohn +1

Equivariant representation learning aims to capture variations induced by input transformations in the representation space, whereas invariant representation learning encodes seman…

cs.CV2025

Enhancing Compositional Reasoning in CLIP via Reconstruction and Alignment of Text Descriptions

Jihoon Kwon, Kyle Min, Jy-yong Sohn

Despite recent advances, vision-language models trained with standard contrastive objectives still struggle with compositional reasoning -- the ability to understand structured rel…

cs.LG2025

On the Similarities of Embeddings in Contrastive Learning

Chungpa Lee, Sehee Lim, Kibok Lee +1

Contrastive learning operates on a simple yet effective principle: Embeddings of positive pairs are pulled together, while those of negative pairs are pushed apart. In this paper,…

cs.LG2025

Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective

Joonkyu Kim, Yejin Kim, Jy-yong Sohn

In continual learning scenarios, catastrophic forgetting of previously learned tasks is a critical issue, making it essential to effectively measure such forgetting. Recently, ther…

cs.IR2025★ 2 cited

FinDER: Financial Dataset for Question Answering and Evaluating Retrieval-Augmented Generation

Chanyeol Choi, Jihoon Kwon, Jaeseon Ha +5

In the fast-paced financial domain, accurate and up-to-date information is critical to addressing ever-evolving market conditions. Retrieving this information correctly is essentia…