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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.…
BRACE: A Benchmark for Robust Audio Caption Quality Evaluation
Tianyu Guo, Hongyu Chen, Hao Liang +5
Automatic audio captioning is essential for audio understanding, enabling applications such as accessibility and content indexing. However, evaluating the quality of audio captions…
Rethinking Text-to-SQL: Dynamic Multi-turn SQL Interaction for Real-world Database Exploration
Linzhuang Sun, Tianyu Guo, Hao Liang +6
Recent advances in Text-to-SQL have achieved strong results in static, single-turn tasks, where models generate SQL queries from natural language questions. However, these systems…
Text2SQL-Flow: A Robust SQL-Aware Data Augmentation Framework for Text-to-SQL
Qifeng Cai, Hao Liang, Chang Xu +3
The data-centric paradigm has emerged as a pivotal direction in artificial intelligence (AI), emphasizing the role of high-quality training data. This shift is especially critical…
DARO: Difficulty-Aware Reweighting Policy Optimization
Jingyu Zhou, Lu Ma, Hao Liang +3
Recent advances in large language models (LLMs) have shown that reasoning ability can be significantly enhanced through Reinforcement Learning with Verifiable Rewards (RLVR). Group…
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…
PilotRL: Training Language Model Agents via Global Planning-Guided Progressive Reinforcement Learning
Keer Lu, Chong Chen, Bin Cui +2
Large Language Models (LLMs) have shown remarkable advancements in tackling agent-oriented tasks. Despite their potential, existing work faces challenges when deploying LLMs in age…
LogicPuzzleRL: Cultivating Robust Mathematical Reasoning in LLMs via Reinforcement Learning
Zhen Hao Wong, Jingwen Deng, Runming He +7
Large language models (LLMs) excel at many supervised tasks but often struggle with structured reasoning in unfamiliar settings. This discrepancy suggests that standard fine-tuning…
Modeling All-Atom Glycan Structures via Hierarchical Message Passing and Multi-Scale Pre-training
Minghao Xu, Jiaze Song, Keming Wu +3
Understanding the various properties of glycans with machine learning has shown some preliminary promise. However, previous methods mainly focused on modeling the backbone structur…
Text2VectorSQL: Towards a Unified Interface for Vector Search and SQL Queries
Zhengren Wang, Dongwen Yao, Bozhou Li +7
The proliferation of unstructured data poses a fundamental challenge to traditional database interfaces. While Text-to-SQL has democratized access to structured data, it remains in…
Learning What Reinforcement Learning Can't: Interleaved Online Fine-Tuning for Hardest Questions
Lu Ma, Hao Liang, Meiyi Qiang +9
Recent advances in large language model (LLM) reasoning have shown that sophisticated behaviors such as planning and self-reflection can emerge through reinforcement learning (RL).…
LoVR: A Benchmark for Long Video Retrieval in Multimodal Contexts
Qifeng Cai, Hao Liang, Zhaoyang Han +6
Long videos contain a vast amount of information, making video-text retrieval an essential and challenging task in multimodal learning. However, existing benchmarks suffer from lim…
Let's Verify Math Questions Step by Step
Chengyu Shen, Zhen Hao Wong, Runming He +8
Large Language Models (LLMs) have recently achieved remarkable progress in mathematical reasoning. To enable such capabilities, many existing works distill strong reasoning models…
Evaluating and Predicting Distorted Human Body Parts for Generated Images
Lu Ma, Kaibo Cao, Hao Liang +6
Recent advancements in text-to-image (T2I) models enable high-quality image synthesis, yet generating anatomically accurate human figures remains challenging. AI-generated images f…
Transfer learning in Scalable Graph Neural Network for Improved Physical Simulation
Siqi Shen, Yu Liu, Daniel Biggs +5
In recent years, Graph Neural Network (GNN) based models have shown promising results in simulating physics of complex systems. However, training dedicated graph network based phys…
MathDebugger: Detecting and Diagnosing Errors in Synthetic Mathematical Data
Hao Liang, Meiyi Qiang, Yuying Li +7
Synthetic mathematical data has become an important resource for scaling the reasoning capabilities of large language models, yet errors in generated questions and solutions can su…