4 citations · 4 across the 8 of their papers we have counts for
8 papers
Diagnosing Harmful Continuation in Answer-Correct Long-CoT Training Traces
Chen He, Yuhao Wu, Lei Wang +2
Long chain-of-thought (CoT) traces are widely used as supervision for reasoning-oriented LLM SFT, yet answer-correct traces can still lead to markedly different fine-tuning outcome…
Multimodal Learning on Low-Quality Data with Conformal Predictive Self-Calibration
Xun Jiang, Yufan Gu, Disen Hu +5
Multimodal learning often grapples with the challenge of low-quality data, which predominantly manifests as two facets: modality imbalance and noisy corruption. While these issues…
What Makes Reasoning Invalid: Echo Reflection Mitigation for Large Language Models
Chen He, Xun Jiang, Lei Wang +5
Large Language Models (LLMs) have demonstrated remarkable performance across a wide range of reasoning tasks. Recent methods have further improved LLM performance in complex mathem…
Conformal Lesion Segmentation for 3D Medical Images
Binyu Tan, Zhiyuan Wang, Jinhao Duan +4
Medical image segmentation serves as a critical component of precision medicine, enabling accurate localization and delineation of pathological regions, such as lesions. However, e…
Truth in the Few: High-Value Data Selection for Efficient Multi-Modal Reasoning
Shenshen Li, Xing Xu, Kaiyuan Deng +3
While multi-modal large language models (MLLMs) have made significant progress in complex reasoning tasks via reinforcement learning, it is commonly believed that extensive trainin…
Anti-Collapse Loss for Deep Metric Learning Based on Coding Rate Metric
Xiruo Jiang, Yazhou Yao, Xili Dai +3
Deep metric learning (DML) aims to learn a discriminative high-dimensional embedding space for downstream tasks like classification, clustering, and retrieval. Prior literature pre…
Dual Dynamic Threshold Adjustment Strategy for Deep Metric Learning
Xiruo Jiang, Yazhou Yao, Sheng Liu +3
Loss functions and sample mining strategies are essential components in deep metric learning algorithms. However, the existing loss function or mining strategy often necessitate th…
BatchNorm-based Weakly Supervised Video Anomaly Detection
Yixuan Zhou, Yi Qu, Xing Xu +3
In weakly supervised video anomaly detection (WVAD), where only video-level labels indicating the presence or absence of abnormal events are available, the primary challenge arises…