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20232026
most citedA Comprehensive Survey on Imbalanced Data Learning

16 citations · 37 across the 16 of their papers we have counts for

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9 papers · 1 filter

cs.LG2025

DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI

Hao Liang, Xiaochen Ma, Zhou Liu +32

The rapidly growing demand for high-quality data in Large Language Models (LLMs) has intensified the need for scalable, reliable, and semantically rich data preparation pipelines.…

cs.LG2025

VADE: Variance-Aware Dynamic Sampling via Online Sample-Level Difficulty Estimation for Multimodal RL

Zengjie Hu, Jiantao Qiu, Tianyi Bai +5

Group-based policy optimization methods like GRPO and GSPO have become standard for training multimodal models, leveraging group-wise rollouts and relative advantage estimation. Ho…

cs.CL2025

Heterogeneous Adaptive Policy Optimization: Tailoring Optimization to Every Token's Nature

Zheng Liu, Mengjie Liu, Siwei Wen +4

Using entropy as a measure of heterogeneity to guide optimization has emerged as a crucial research direction in Reinforcement Learning for LLMs. However, existing methods typicall…

cs.CV2025

Native Visual Understanding: Resolving Resolution Dilemmas in Vision-Language Models

Junbo Niu, Yuanhong Zheng, Ziyang Miao +8

Vision-Language Models (VLMs) face significant challenges when dealing with the diverse resolutions and aspect ratios of real-world images, as most existing models rely on fixed, l…

cs.CV2025

Multi-Step Visual Reasoning with Visual Tokens Scaling and Verification

Tianyi Bai, Zengjie Hu, Fupeng Sun +7

Multi-modal large language models (MLLMs) have achieved remarkable capabilities by integrating visual perception with language understanding, enabling applications such as image-gr…

cs.CV2025

Hallucination at a Glance: Controlled Visual Edits and Fine-Grained Multimodal Learning

Tianyi Bai, Yuxuan Fan, Jiantao Qiu +7

Multimodal large language models (MLLMs) have achieved strong performance on vision-language tasks but still struggle with fine-grained visual differences, leading to hallucination…

cs.CL2025

SAS-Bench: A Fine-Grained Benchmark for Evaluating Short Answer Scoring with Large Language Models

Peichao Lai, Kexuan Zhang, Yi Lin +8

Subjective Answer Grading (SAG) plays a crucial role in education, standardized testing, and automated assessment systems, particularly for evaluating short-form responses in Short…

cs.CV2025

FLARE: Fully Integration of Vision-Language Representations for Deep Cross-Modal Understanding

Zheng Liu, Mengjie Liu, Jingzhou Chen +4

We introduce FLARE, a family of vision language models (VLMs) with a fully vision-language alignment and integration paradigm. Unlike existing approaches that rely on single MLP pr…

cs.LG2025★ 16 cited

A Comprehensive Survey on Imbalanced Data Learning

Xinyi Gao, Dongting Xie, Yihang Zhang +5

With the expansion of data availability, machine learning (ML) has achieved remarkable breakthroughs in both academia and industry. However, imbalanced data distributions are preva…