activity
20232026
most citedLightweight Embeddings for Graph Collaborative Filtering

2 citations · 6 across the 38 of their papers we have counts for

collaborators

57 papers

cs.IR2026

Empowering Compact LLMs with Fusion of Layer-wise Exits for Recommendation

Xurong Liang, Tong Chen, Quoc Viet Hung Nguyen +3

Large language model-based recommender systems (LLM-RSs) have demonstrated remarkable capabilities, but are computationally unsustainable for many real-world applications. Compact…

cs.AI2026

ODYSSE: Episode-wise Policy Optimization for Personalized Agentic Reasoning

Jiaqi Zhang, Tong Chen, Junliang Yu +2

Agentic systems have rapidly advanced in their ability to interact with real-world environments, leverage external tools, and provide services for users. However, unlike natural-wo…

cs.IR2026

VaLiDRec: Variable-Length LLM-Aligned Semantic IDs for Generative Recommendation

Shutong Qiao, Wei Yuan, Tong Chen +3

Generative recommendation commonly represents items using fixed-length semantic identifiers (SIDs) constructed through clustering and quantization. However, these artificial codes…

cs.IR2026

FOSTER: First-order Dataset Distillation for Text-based Sequential Recommendation

Hung Vinh Tran, Tong Chen, Xinyi Gao +3

Text-based sequential recommender systems, while greatly improving recommendation accuracy by incorporating item contexts, are undeniably more expensive to train. By condensing a l…

cs.LG2026

GRAFT: Graph-Tokenized LLMs for Tool Planning

Xinyi Gao, Xinyu Ren, Junliang Yu +3

Large language models (LLMs) are increasingly used to complete complex tasks by selecting and coordinating external tools across multiple steps. This requires aligning tool choices…

cs.LG2026

Efficient Prompt Learning for Traffic Forecasting

Qianru Zhang, Xinyi Gao, Alexander Zhou +3

Accurate traffic prediction is essential for optimizing transportation systems, enhancing resource allocation, and improving overall urban administration. Spatio-temporal graph neu…