8 papers
EXPO-SQL: Execution-based Clause-level Policy Optimization for Text-to-SQL
Jaehoon Lee, CheolWon Na, Suyoung Bae +4
Text-to-SQL enables users to query databases using natural language by generating executable SQL queries. Recent methods have increasingly adopted Large Language Models based reinf…
CountCluster: Training-Free Object Quantity Guidance with Cross-Attention Map Clustering for Text-to-Image Generation
Joohyeon Lee, Jin-Seop Lee, Jee-Hyong Lee
Diffusion-based text-to-image generation models have demonstrated strong performance in terms of image quality and diversity. However, they still struggle to generate images that a…
Learning to Refuse: Refusal-Aware Reinforcement Fine-Tuning for Hard-Irrelevant Queries in Video Temporal Grounding
Jin-Seop Lee, SungJoon Lee, SeongJun Jung +2
Video Temporal Grounding (VTG) aims to localize a temporal segment in a video corresponding to a natural language query. However, existing VTG models assume that a relevant segment…
BD-Net: Has Depth-Wise Convolution Ever Been Applied in Binary Neural Networks?
DoYoung Kim, Jin-Seop Lee, Noo-ri Kim +2
Recent advances in model compression have highlighted the potential of low-bit precision techniques, with Binary Neural Networks (BNNs) attracting attention for their extreme effic…
Stabilizing Open-Set Test-Time Adaptation via Primary-Auxiliary Filtering and Knowledge-Integrated Prediction
Byung-Joon Lee, Jin-Seop Lee, Jee-Hyong Lee
Deep neural networks demonstrate strong performance under aligned training-test distributions. However, real-world test data often exhibit domain shifts. Test-Time Adaptation (TTA)…
TAG: A Simple Yet Effective Temporal-Aware Approach for Zero-Shot Video Temporal Grounding
Jin-Seop Lee, SungJoon Lee, Jaehan Ahn +2
Video Temporal Grounding (VTG) aims to extract relevant video segments based on a given natural language query. Recently, zero-shot VTG methods have gained attention by leveraging…