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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★ 2 cited
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…