1 citations · 1 across the 34 of their papers we have counts for
8 papers · 2 filters
Efficient RAG with Intent-Aware Retrieval and Semantics-Preserving Chunking
Fachrina Dewi Puspitasari, Chaoning Zhang, Jiaquan Zhang +6
The demand for powerful instruction following and reasoning capability of large language models (LLMs) has promoted rapid development of retrieval-augmented generation (RAG). The R…
DASH-KV: Accelerating Long-Context LLM Inference via Asymmetric KV Cache Hashing
Jinyu Guo, Zhihan Zhang, Jiehui Xie +7
The quadratic computational complexity of the standard attention mechanism constitutes a fundamental bottleneck for large language models in long-context inference. While existing…
From Similarity to Structure: Training-free LLM Context Compression with Hybrid Graph Priors
Yitian Zhou, Chaoning Zhang, Jiaquan Zhang +6
Long-context large language models remain computationally expensive to run and often fail to reliably process very long inputs, which makes context compression an important compone…
Small Language Model Helps Resolve Semantic Ambiguity of LLM Prompt
Zhenzhen Huang, Chaoning Zhang, Fachrina Dewi Puspitasari +4
Large language models (LLMs) are increasingly utilized in various complex reasoning tasks due to their excellent instruction following capability. However, the model's performance…
Transforming External Knowledge into Triplets for Enhanced Retrieval in RAG of LLMs
Xudong Wang, Chaoning Zhang, Qigan Sun +7
Retrieval-Augmented Generation (RAG) mitigates hallucination in large language models (LLMs) by incorporating external knowledge during generation. However, the effectiveness of RA…
TDA-RC: Task-Driven Alignment for Knowledge-Based Reasoning Chains in Large Language Models
Jiaquan Zhang, Qigan Sun, Chaoning Zhang +11
Enhancing the reasoning capability of large language models (LLMs) remains a core challenge in natural language processing. The Chain-of-Thought (CoT) paradigm dominates practical…
Optimizing Soft Prompt Tuning via Structural Evolution
Zhenzhen Huang, Chaoning Zhang, Haoyu Bian +8
Soft prompt tuning leverages continuous embeddings to capture task-specific information in large pre-trained language models (LLMs), achieving competitive performance in few-shot s…
Text summarization via global structure awareness
Jiaquan Zhang, Chaoning Zhang, Shuxu Chen +9
Text summarization is a fundamental task in natural language processing (NLP), and the information explosion has made long-document processing increasingly demanding, making summar…