activity
20232025
most citedMeKB-Rec: Personal Knowledge Graph Learning for Cross-Domain Recommendation

1 citations · 1 across the 4 of their papers we have counts for

collaborators

10 papers

cs.IR2025

LexSemBridge: Fine-Grained Dense Representation Enhancement through Token-Aware Embedding Augmentation

Shaoxiong Zhan, Hai Lin, Hongming Tan +6

As queries in retrieval-augmented generation (RAG) pipelines powered by large language models (LLMs) become increasingly complex and diverse, dense retrieval models have demonstrat…

cs.CV2025

On the Perception Bottleneck of VLMs for Chart Understanding

Junteng Liu, Weihao Zeng, Xiwen Zhang +3

Chart understanding requires models to effectively analyze and reason about numerical data, textual elements, and complex visual components. Our observations reveal that the percep…

cs.CL2025

DAST: Context-Aware Compression in LLMs via Dynamic Allocation of Soft Tokens

Shaoshen Chen, Yangning Li, Zishan Xu +4

Large Language Models (LLMs) face computational inefficiencies and redundant processing when handling long context inputs, prompting a focus on compression techniques. While existi…

cs.CL2024

Loss-Aware Curriculum Learning for Chinese Grammatical Error Correction

Ding Zhang, Yangning Li, Lichen Bai +6

Chinese grammatical error correction (CGEC) aims to detect and correct errors in the input Chinese sentences. Recently, Pre-trained Language Models (PLMS) have been employed to imp…

cs.AI2024

B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners

Weihao Zeng, Yuzhen Huang, Lulu Zhao +3

In the absence of extensive human-annotated data for complex reasoning tasks, self-improvement -- where models are trained on their own outputs -- has emerged as a primary method f…

cs.IR2024

Firzen: Firing Strict Cold-Start Items with Frozen Heterogeneous and Homogeneous Graphs for Recommendation

Hulingxiao He, Xiangteng He, Yuxin Peng +2

Recommendation models utilizing unique identities (IDs) to represent distinct users and items have dominated the recommender systems literature for over a decade. Since multi-modal…