14 citations · 25 across the 17 of their papers we have counts for
19 papers
Draft-Refine-Optimize: Self-Evolved Learning for Natural Language to MongoDB Query Generation
Mingwei Ye, Jiaxi Zhuang, Mingjun Xu +3
Natural Language to MongoDB Query Language (NL2MQL) is essential for democratizing access to modern document-centric databases. Unlike Text-to-SQL, NL2MQL faces unique challenges f…
SpecXMaster Technical Report
Yutang Ge, Yaning Cui, Hanzheng Li +15
Intelligent spectroscopy serves as a pivotal element in AI-driven closed-loop scientific discovery, functioning as the critical bridge between matter structure and artificial intel…
AirNav: A Large-Scale UAV Vision-and-Language Navigation Dataset with Natural and Diverse Instructions
Hengxing Cai, Yijie Rao, Ligang Huang +7
Existing UAV vision-and-language navigation (VLN) benchmarks rarely provide realistic aerial scenes, natural process-level instructions, and sufficient scale simultaneously, making…
Reasoning-Enhanced Large Language Models for Molecular Property Prediction
Jiaxi Zhuang, Yaorui Shi, Jue Hou +8
Molecular property prediction is crucial for drug discovery and materials science, yet existing approaches suffer from limited interpretability, poor cross-task generalization, and…
Look Back to Reason Forward: Revisitable Memory for Long-Context LLM Agents
Yaorui Shi, Yuxin Chen, Siyuan Wang +5
Large language models face challenges in long-context question answering, where key evidence of a query may be dispersed across millions of tokens. Existing works equip large langu…
Interpretable Reward Model via Sparse Autoencoder
Shuyi Zhang, Wei Shi, Sihang Li +3
Large language models (LLMs) have been widely deployed across numerous fields. Reinforcement Learning from Human Feedback (RLHF) leverages reward models (RMs) as proxies for human…
MolReasoner: Toward Effective and Interpretable Reasoning for Molecular LLMs
Guojiang Zhao, Zixiang Lu, Yutang Ge +13
Large Language Models (LLMs) have shown impressive performance across various domains, but their ability to perform molecular reasoning remains underexplored. Existing methods most…
SA-GCS: Semantic-Aware Gaussian Curriculum Scheduling for UAV Vision-Language Navigation
Hengxing Cai, Jinhan Dong, Yijie Rao +8
Unmanned Aerial Vehicle (UAV) Vision-Language Navigation (VLN) aims to enable agents to accurately localize targets and plan flight paths in complex environments based on natural l…
MM-R5: MultiModal Reasoning-Enhanced ReRanker via Reinforcement Learning for Document Retrieval
Mingjun Xu, Jinhan Dong, Jue Hou +5
Multimodal document retrieval systems enable information access across text, images, and layouts, benefiting various domains like document-based question answering, report analysis…
Doc2SAR: A Synergistic Framework for High-Fidelity Extraction of Structure-Activity Relationships from Scientific Documents
Jiaxi Zhuang, Kangning Li, Jue Hou +3
Extracting molecular structure-activity relationships (SARs) from scientific literature and patents is essential for drug discovery and materials research. However, this task remai…
FlightGPT: Towards Generalizable and Interpretable UAV Vision-and-Language Navigation with Vision-Language Models
Hengxing Cai, Jinhan Dong, Jingjun Tan +7
Unmanned Aerial Vehicle (UAV) Vision-and-Language Navigation (VLN) is vital for applications such as disaster response, logistics delivery, and urban inspection. However, existing…
A Multi-Granularity Retrieval Framework for Visually-Rich Documents
Mingjun Xu, Zehui Wang, Hengxing Cai +1
Retrieval-augmented generation (RAG) systems have predominantly focused on text-based retrieval, limiting their effectiveness in handling visually-rich documents that encompass tex…
Search and Refine During Think: Facilitating Knowledge Refinement for Improved Retrieval-Augmented Reasoning
Yaorui Shi, Sihang Li, Chang Wu +5
Large language models have demonstrated impressive reasoning capabilities but are inherently limited by their knowledge reservoir. Retrieval-augmented reasoning mitigates this limi…
Towards Unified and Lossless Latent Space for 3D Molecular Latent Diffusion Modeling
Yanchen Luo, Zhiyuan Liu, Yi Zhao +6
3D molecule generation is crucial for drug discovery and material science, requiring models to process complex multi-modalities, including atom types, chemical bonds, and 3D coordi…
Intelligent System for Automated Molecular Patent Infringement Assessment
Yaorui Shi, Sihang Li, Taiyan Zhang +12
Automated drug discovery offers significant potential for accelerating the development of novel therapeutics by substituting labor-intensive human workflows with machine-driven pro…
SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding
Sihang Li, Jin Huang, Jiaxi Zhuang +7
Scientific literature understanding is crucial for extracting targeted information and garnering insights, thereby significantly advancing scientific discovery. Despite the remarka…
Uni-SMART: Universal Science Multimodal Analysis and Research Transformer
Hengxing Cai, Xiaochen Cai, Shuwen Yang +14
In scientific research and its application, scientific literature analysis is crucial as it allows researchers to build on the work of others. However, the fast growth of scientifi…
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis
Hengxing Cai, Xiaochen Cai, Junhan Chang +20
Recent breakthroughs in Large Language Models (LLMs) have revolutionized scientific literature analysis. However, existing benchmarks fail to adequately evaluate the proficiency of…
Self-Supervised Exploration via Temporal Inconsistency in Reinforcement Learning
Zijian Gao, Kele Xu, Yuanzhao Zhai +4
Under sparse extrinsic reward settings, reinforcement learning has remained challenging, despite surging interests in this field. Previous attempts suggest that intrinsic reward ca…