1 citations · 2 across the 8 of their papers we have counts for
10 papers
ESCAPE: Egocentric Sensing for Collision Avoidance and Policy Execution
Weiqing Shen, Wenhao Huang, Baokang Zhang +5
Motion planning in unstructured environments is a bottleneck for robot deployment. Current visuomotor policies predominantly rely on external cameras, introducing perceptual blind…
ResKV: Reconstructing Omitted Attention Contributions for Fixed-Budget KV Cache Compression
Yuhang Zhan, Lisi Chen, Shuo Shang
KV cache compression is essential for efficient long-context inference. Existing eviction methods permanently discard unselected tokens and consequently remove their aggregate cont…
From GPS Points to Travel Patterns: Flexible and Semantic Trajectory Generation with LLMs
Silin Zhou, Chenhao Wang, Yuntao Wen +3
Urban trajectories play a crucial role in modeling urban dynamics and supporting various smart city applications. However, privacy concerns restrict access to large-scale and high-…
Efficient Model-Agnostic Continual Learning for Next POI Recommendation
Chenhao Wang, Shanshan Feng, Lisi Chen +2
Next point-of-interest (POI) recommendation improves personalized location-based services by predicting users' next destinations based on their historical check-ins. However, most…
Region-Point Joint Representation for Effective Trajectory Similarity Learning
Hao Long, Silin Zhou, Lisi Chen +1
Recent learning-based methods have reduced the computational complexity of traditional trajectory similarity computation, but state-of-the-art (SOTA) methods still fail to leverage…
RED: Effective Trajectory Representation Learning with Comprehensive Information
Silin Zhou, Shuo Shang, Lisi Chen +2
Trajectory representation learning (TRL) maps trajectories to vectors that can then be used for various downstream tasks, including trajectory similarity computation, trajectory cl…
Grid and Road Expressions Are Complementary for Trajectory Representation Learning
Silin Zhou, Shuo Shang, Lisi Chen +2
Trajectory representation learning (TRL) maps trajectories to vectors that can be used for many downstream tasks. Existing TRL methods use either grid trajectories, capturing movem…
DRE: Generating Recommendation Explanations by Aligning Large Language Models at Data-level
Shen Gao, Yifan Wang, Jiabao Fang +3
Recommendation systems play a crucial role in various domains, suggesting items based on user behavior.However, the lack of transparency in presenting recommendations can lead to u…
360REA: Towards A Reusable Experience Accumulation with 360° Assessment for Multi-Agent System
Shen Gao, Hao Li, Chengrui Huang +4
Large language model agents have demonstrated remarkable advancements across various complex tasks. Recent works focus on optimizing the agent team or employing self-reflection to…
Not All Layers of LLMs Are Necessary During Inference
Siqi Fan, Xin Jiang, Xiang Li +6
Due to the large number of parameters, the inference phase of Large Language Models (LLMs) is resource-intensive. However, not all requests posed to LLMs are equally difficult to h…