6 citations · 8 across the 8 of their papers we have counts for
10 papers
GSM: Efficient Language Modeling with Shared Global State
Yunao Zheng, Bin Wen, Xiaojie Wang +12
Improving language model efficiency requires not only cheaper operations but also eliminating redundant computation. We argue that effective modeling requires information accessibi…
Lngram v2: Latent N-Gram Memory with Interpretable Discrete Representations
Yunao Zheng, Bin Wen, Xiaojie Wang +12
Transformers lack a native lookup mechanism, requiring repeated dense computation to recognize and reuse local static patterns. Lngram v1 introduces tokenizer-independent condition…
Lngram: N-gram Conditional Memory in Latent Space
Yunao Zheng, Guoyang Xia, Xiaojie Wang +1
Sequence modeling requires both compositional reasoning and local static knowledge retrieval, yet standard Transformers handle both through dense computation. Engram partially deco…
ROSA-Tuning: Enhancing Long-Context Modeling via Suffix Matching
Yunao Zheng, Xiaojie Wang, Lei Ren +1
Long-context capability and computational efficiency are among the central challenges facing today's large language models. Existing efficient attention methods reduce computationa…
DynImg: Key Frames with Visual Prompts are Good Representation for Multi-Modal Video Understanding
Xiaoyi Bao, Chenwei Xie, Hao Tang +4
In recent years, the introduction of Multi-modal Large Language Models (MLLMs) into video understanding tasks has become increasingly prevalent. However, how to effectively integra…
Aligned Better, Listen Better for Audio-Visual Large Language Models
Yuxin Guo, Shuailei Ma, Shijie Ma +7
Audio is essential for multimodal video understanding. On the one hand, video inherently contains audio, which supplies complementary information to vision. Besides, video large la…
CoReS: Orchestrating the Dance of Reasoning and Segmentation
Xiaoyi Bao, Siyang Sun, Shuailei Ma +5
The reasoning segmentation task, which demands a nuanced comprehension of intricate queries to accurately pinpoint object regions, is attracting increasing attention. However, Mult…
Dual Mean-Teacher: An Unbiased Semi-Supervised Framework for Audio-Visual Source Localization
Yuxin Guo, Shijie Ma, Hu Su +5
Audio-Visual Source Localization (AVSL) aims to locate sounding objects within video frames given the paired audio clips. Existing methods predominantly rely on self-supervised con…
Relevant Intrinsic Feature Enhancement Network for Few-Shot Semantic Segmentation
Xiaoyi Bao, Jie Qin, Siyang Sun +2
For few-shot semantic segmentation, the primary task is to extract class-specific intrinsic information from limited labeled data. However, the semantic ambiguity and inter-class s…
Understanding the Multi-modal Prompts of the Pre-trained Vision-Language Model
Shuailei Ma, Chen-Wei Xie, Ying Wei +5
Prompt learning has emerged as an efficient alternative for fine-tuning foundational models, such as CLIP, for various downstream tasks. However, there is no work that provides a c…