24 citations · 52 across the 15 of their papers we have counts for
16 papers
Infinity-Parser2 Technical Report
Zuming Huang, Jun Huang, Kexuan Ren +12
We present Infinity-Parser2, a large multimodal model that couples a controllable data-synthesis pipeline with multi-task reinforcement learning for end-to-end document parsing, ad…
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…
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…
Structure-aware Semantic Discrepancy and Consistency for 3D Medical Image Self-supervised Learning
Tan Pan, Zhaorui Tan, Kaiyu Guo +6
3D medical image self-supervised learning (mSSL) holds great promise for medical analysis. Effectively supporting broader applications requires considering anatomical structure var…
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…
To Code or not to Code? Adaptive Tool Integration for Math Language Models via Expectation-Maximization
Haozhe Wang, Long Li, Chao Qu +4
Recent advances in mathematical problem-solving with language models (LMs) integrate chain-of-thought (CoT) reasoning and code execution to harness their complementary strengths. H…
OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Siming Huang, Tianhao Cheng, J. K. Liu +16
Large language models (LLMs) for code have become indispensable in various domains, including code generation, reasoning tasks and agent systems. While open-access code LLMs are in…
Thought-Like-Pro: Enhancing Reasoning of Large Language Models through Self-Bootstrapped Prolog-based Chain-of-Thought
Xiaoyu Tan, Yongxin Deng, Xihe Qiu +7
Large language models have demonstrated remarkable capabilities as general-purpose assistants, excelling in a wide range of reasoning tasks and supporting various aspects of daily…
Denoising Time Cycle Modeling for Recommendation
Sicong Xie, Qunwei Li, Weidi Xu +3
Recently, modeling temporal patterns of user-item interactions have attracted much attention in recommender systems. We argue that existing methods ignore the variety of temporal p…
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…
Question Directed Graph Attention Network for Numerical Reasoning over Text
Kunlong Chen, Weidi Xu, Xingyi Cheng +6
Numerical reasoning over texts, such as addition, subtraction, sorting and counting, is a challenging machine reading comprehension task, since it requires both natural language un…
SpellGCN: Incorporating Phonological and Visual Similarities into Language Models for Chinese Spelling Check
Xingyi Cheng, Weidi Xu, Kunlong Chen +5
Chinese Spelling Check (CSC) is a task to detect and correct spelling errors in Chinese natural language. Existing methods have made attempts to incorporate the similarity knowledg…
Symmetric Regularization based BERT for Pair-wise Semantic Reasoning
Weidi Xu, Xingyi Cheng, Kunlong Chen +7
The ability of semantic reasoning over the sentence pair is essential for many natural language understanding tasks, e.g., natural language inference and machine reading comprehens…
Variational Semi-supervised Aspect-term Sentiment Analysis via Transformer
Xingyi Cheng, Weidi Xu, Taifeng Wang +1
Aspect-term sentiment analysis (ATSA) is a longstanding challenge in natural language understanding. It requires fine-grained semantical reasoning about a target entity appeared in…
Variational Autoencoders for Semi-supervised Text Classification
Weidi Xu, Haoze Sun, Chao Deng +1
Although semi-supervised variational autoencoder (SemiVAE) works in image classification task, it fails in text classification task if using vanilla LSTM as its decoder. From a per…