26 citations · 75 across the 30 of their papers we have counts for
14 papers · 1 filter
Beyond Successor Accuracy: State Retention for Recursive Self-Improvement in Recommendation
Jinfeng Xu, Zheyu Chen, Ziyue Peng +5
Recommendation recursive self-improvement (Rec-RSI) feeds recommender outputs into subsequent training. Evaluating each round solely through its latest model assumes that the succe…
Agents as Knowledge Integrator and Utilizer in Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +9
Online platforms increasingly rely on multimodal recommender systems to rank products, media, and other Web content. Existing methods usually inject visual and textual features int…
Neural Tree Collaborative Filtering: Rethinking Graph Collaborative Filtering as Tree Collaborative Filtering with Curvature-Aware Propagation Depth
Jinfeng Xu, Zheyu Chen, Ziyue Peng +5
Graph Collaborative Filtering (GCF) has become the dominant paradigm in modern recommender systems by modeling user-item interactions as a bipartite graph and propagating embedding…
F2STNet: Fair and Federated Spectral-Temporal Modeling for Graph Forecasting
Jiayi Zhang, Jinfeng Xu, Hewei Wang +7
Spatiotemporal prediction on graph-structured data is central to traffic forecasting and environmental monitoring, yet decentralized and heterogeneous data complicate both sequence…
One Graph, Multiple Gains: Single High-Quality Item-Item Graph for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Ziyue Peng +6
Multimodal recommendation leverages item multimodal features alongside collaborative signals to capture user preferences. While item-item graphs have become a key building block in…
LATTE: Forecasting Peer Anchored Preference Trajectories for Personalized LLM Generation
Jinze Li, Xiaoyan Yang, Shuo Yang +5
Personalized generation with frozen large language models requires a conditioning signal that is both compact and current. Existing personalization methods typically retrieve or su…
Beyond the Target: From Imitation to Collaboration in Speculative Decoding
Jinze Li, Yixing Xu, Guanchen Li +7
Speculative decoding (SPD) accelerates large language model (LLM) inference by letting a smaller draft model propose multiple future tokens that are verified in parallel by a large…
Belief-Guided Inference Control for Large Language Model Services via Verifiable Observations
Wenhao Yuan, Chenchen Lin, Jian Chen +3
In black-box large language model (LLM) services, response reliability is often only partially observable at decision time, while stronger inference pathways incur substantial comp…
OCR-Memory: Optical Context Retrieval for Long-Horizon Agent Memory
Jinze Li, Yang Zhang, Xin Yang +5
Autonomous LLM agents increasingly operate in long-horizon, interactive settings where success depends on reusing experience accumulated over extended histories. However, existing…
Well Begun is Half Done: Training-Free and Model-Agnostic Semantically Guaranteed User Representation Initialization for Multimodal Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +6
Recent advancements in multimodal recommendations, which leverage diverse modality information to mitigate data sparsity and improve recommendation accuracy, have gained significan…
DBGL: Decay-aware Bipartite Graph Learning for Irregular Medical Time Series Classification
Jian Chen, Yuzhu Hu, Xiaoyan Yuan +6
Irregular Medical Time Series play a critical role in the clinical domain to better understand the patient's condition. However, inherent irregularity arising from heterogeneous sa…
Verify Before You Commit: Towards Faithful Reasoning in LLM Agents via Self-Auditing
Wenhao Yuan, Chenchen Lin, Jian Chen +3
In large language model (LLM) agents, reasoning trajectories are treated as reliable internal beliefs for guiding actions and updating memory. However, coherent reasoning can still…
CAMMSR: Category-Guided Attentive Mixture of Experts for Multimodal Sequential Recommendation
Jinfeng Xu, Zheyu Chen, Shuo Yang +6
The explosion of multimedia data in information-rich environments has intensified the challenges of personalized content discovery, positioning recommendation systems as an essenti…
Reinforced Curriculum Pre-Alignment for Domain-Adaptive VLMs
Yuming Yan, Shuo Yang, Kai Tang +7
Vision-Language Models (VLMs) demonstrate remarkable general-purpose capabilities but often fall short in specialized domains such as medical imaging or geometric problem-solving.…