2 citations · 4 across the 10 of their papers we have counts for
7 papers · 1 filter
VisualRouter: Query-Grounded Visual Sampling for Long Video Understanding
Haiyue Zhang, Yi Bin, Xun Jiang +5
Large vision-language models (LVLMs) have achieved significant progress in video understanding, yet understanding long videos remains challenging due to the large number of visual…
MASRA: MLLM-Assisted Semantic-Relational Consistent Alignment for Video Temporal Grounding
Ran Ran, Jiwei Wei, Shuchang Zhou +5
Video Temporal Grounding (VTG) faces a cross-modal semantic gap that often leads to background features being incorrectly aligned with the query, while directly matching the query…
CARD: Non-Uniform Quantization of Visual Semantic Unit for Generative Recommendation
Yibiao Wei, Jie Zou, Pengfei Zhang +4
Generative recommendation frameworks typically represent items as discrete Semantic IDs (SIDs). While existing studies have sought to enhance SID construction by incorporating mult…
Transforming External Knowledge into Triplets for Enhanced Retrieval in RAG of LLMs
Xudong Wang, Chaoning Zhang, Qigan Sun +7
Retrieval-Augmented Generation (RAG) mitigates hallucination in large language models (LLMs) by incorporating external knowledge during generation. However, the effectiveness of RA…
TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Models
Jiaquan Zhang, Qigan Sun, Chaoning Zhang +11
Enhancing the reasoning capability of large language models (LLMs) remains a core challenge in natural language processing. The Chain-of-Thought (CoT) paradigm dominates practical…
UFO-4D: Unposed Feedforward 4D Reconstruction from Two Images
Junhwa Hur, Charles Herrmann, Songyou Peng +4
Dense 4D reconstruction from unposed images remains a critical challenge, with current methods relying on slow test-time optimization or fragmented, task-specific feedforward model…
TP-Spikformer: Token Pruned Spiking Transformer
Wenjie Wei, Xiaolong Zhou, Malu Zhang +8
Spiking neural networks (SNNs) offer an energy-efficient alternative to traditional neural networks due to their event-driven computing paradigm. However, recent advancements in sp…