78 citations · 80 across the 15 of their papers we have counts for
16 papers
SlerpFlow: Spherical Trajectory Correction for Rectified Flow Inversion
Wenbin Duan, Yan Shu, Zhuoyuan Fu +4
Rectified-flow-based diffusion transformers, particularly FLUX, have demonstrated outstanding performance in high-quality image generation. However, achieving fast and accurate inv…
Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Models
Zhuoyuan Fu, Zeshang Li, Yiqiong Zhang +5
While Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in 2D medical image understanding, their extension to 3D volumetric imaging remains hindered by…
Bridging Auxiliary Constraints to Resolve Instruction Following in Large Reasoning Models
Zhengyi Zhao, Shubo Zhang, Huimin Wang +7
Large Reasoning Models (LRMs) have demonstrated impressive capabilities in many tasks, yet they struggle with reliably following multiple instructions, either by failing to satisfy…
Beyond the Literal: Decomposing Pragmatic Intent in Multimodal Meme Understanding
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +6
When asked what a meme or sarcastic post means, Large Vision Language Models (LVLMs) tend to describe what the image shows rather than what the author is trying to communicate. Sta…
Guaranteeing Knowledge Integration with Joint Decoding for Retrieval-Augmented Generation
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +7
Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs) by providing access to external knowledge. However, current research primarily focuses on r…
Step-DeepResearch Technical Report
Chen Hu, Haikuo Du, Heng Wang +64
As LLMs shift toward autonomous agents, Deep Research has emerged as a pivotal metric. However, existing academic benchmarks like BrowseComp often fail to meet real-world demands f…
Dual-Density Inference for Efficient Language Model Reasoning
Zhengyi Zhao, Shubo Zhang, Yuxi Zhang +3
Large Language Models (LLMs) have shown impressive capabilities in complex reasoning tasks. However, current approaches employ uniform language density for both intermediate reason…
MemeReaCon: Probing Contextual Meme Understanding in Large Vision-Language Models
Zhengyi Zhao, Shubo Zhang, Yuxi Zhang +10
Memes have emerged as a popular form of multimodal online communication, where their interpretation heavily depends on the specific context in which they appear. Current approaches…
T: An Adaptive Test-Time Scaling Strategy for Contextual Question Answering
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +7
Recent advances in Large Language Models (LLMs) have demonstrated remarkable performance in Contextual Question Answering (CQA). However, prior approaches typically employ elaborat…
WHERE and WHICH: Iterative Debate for Biomedical Synthetic Data Augmentation
Zhengyi Zhao, Shubo Zhang, Bin Liang +2
In Biomedical Natural Language Processing (BioNLP) tasks, such as Relation Extraction, Named Entity Recognition, and Text Classification, the scarcity of high-quality data remains…
FReM: A Flexible Reasoning Mechanism for Balancing Quick and Slow Thinking in Long-Context Question Answering
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +3
Long-context question-answering (LCQA) systems have greatly benefited from the powerful reasoning capabilities of large language models (LLMs), which can be categorized into slow a…
EventWeave: A Dynamic Framework for Capturing Core and Supporting Events in Dialogue Systems
Zhengyi Zhao, Shubo Zhang, Yiming Du +5
Large language models have improved dialogue systems, but often process conversational turns in isolation, overlooking the event structures that guide natural interactions. Hence w…
Sigma: Differential Rescaling of Query, Key and Value for Efficient Language Models
Zhenghao Lin, Zihao Tang, Xiao Liu +31
We introduce Sigma, an efficient large language model specialized for the system domain, empowered by a novel architecture including DiffQKV attention, and pre-trained on our metic…
GODIVA: Generating Open-DomaIn Videos from nAtural Descriptions
Chenfei Wu, Lun Huang, Qianxi Zhang +5
Generating videos from text is a challenging task due to its high computational requirements for training and infinite possible answers for evaluation. Existing works typically exp…
CHIME: Cross-passage Hierarchical Memory Network for Generative Review Question Answering
Junru Lu, Gabriele Pergola, Lin Gui +2
We introduce CHIME, a cross-passage hierarchical memory network for question answering (QA) via text generation. It extends XLNet introducing an auxiliary memory module consisting…
Context-aware Embedding for Targeted Aspect-based Sentiment Analysis
Bin Liang, Jiachen Du, Ruifeng Xu +2
Attention-based neural models were employed to detect the different aspects and sentiment polarities of the same target in targeted aspect-based sentiment analysis (TABSA). However…