From the 1 of 9 linked papers with an AI index.
9 papers
Infinity-Parser2 Technical Report
Zuming Huang, Jun Huang, Kexuan Ren +12
Infinity-Parser2 is a large multimodal model that uses a controllable synthetic data pipeline and multi‑task reinforcement learning to parse documents, offering two variants (Flash…
SQL-ASTRA: Alleviating Sparse Feedback in Agentic SQL via Column-Set Matching and Trajectory Aggregation
Long Li, Zhijian Zhou, Jiangxuan Long +5
Agentic Reinforcement Learning (RL) shows promise for complex tasks, but Text-to-SQL remains mostly restricted to single-turn paradigms. A primary bottleneck is the credit assignme…
DyJR: Preserving Diversity in Reinforcement Learning with Verifiable Rewards via Dynamic Jensen-Shannon Replay
Long Li, Zhijian Zhou, Tianyi Wang +7
While Reinforcement Learning (RL) enhances Large Language Model reasoning, on-policy algorithms like GRPO are sample-inefficient as they discard past rollouts. Existing experience…
Harnessing Negative Signals: Reinforcement Distillation from Teacher Data for LLM Reasoning
Shuyao Xu, Cheng Peng, Jiangxuan Long +3
Recent advances in model distillation show that data from advanced reasoning models can effectively train smaller student models. However, standard practices discard incorrect reas…
LogicMP: A Neuro-symbolic Approach for Encoding First-order Logic Constraints
Weidi Xu, Jingwei Wang, Lele Xie +7
Integrating first-order logic constraints (FOLCs) with neural networks is a crucial but challenging problem since it involves modeling intricate correlations to satisfy the constra…
Constraints-Guided Diffusion Reasoner for Neuro-Symbolic Learning
Xuan Zhang, Zhijian Zhou, Weidi Xu +3
Enabling neural networks to learn complex logical constraints and fulfill symbolic reasoning is a critical challenge. Bridging this gap often requires guiding the neural network's…