21 citations · 24 across the 12 of their papers we have counts for
12 papers
When Context Misleads: Intent-Guided Decoding for Robust Retrieval-Augmented Generation
Haolin Jin, Pengyue Yang, Huaming Chen
Retrieval-augmented generation (RAG) improves large language models by grounding generation in external evidence, but it also introduces a source trust problem: retrieved context m…
Are LLMs Reliable Code Reviewers? Systematic Overcorrection in Requirement Conformance Judgement
Haolin Jin, Huaming Chen
Large language models (LLMs) have become essential tools in software development, widely used for requirements engineering, code generation and review tasks. Software engineers oft…
Trust in One Round: Confidence Estimation for Large Language Models via Structural Signals
Pengyue Yang, Jiawen Wen, Haolin Jin +3
Large language models (LLMs) are increasingly deployed in domains where errors carry high social, scientific, or safety costs. Yet standard confidence estimators, such as token lik…
Human-aligned AI Model Cards with Weighted Hierarchy Architecture
Pengyue Yang, Haolin Jin, Qingwen Zeng +3
The proliferation of Large Language Models (LLMs) has led to a burgeoning ecosystem of specialized, domain-specific models. While this rapid growth accelerates innovation, it has s…
Uncovering Systematic Failures of LLMs in Verifying Code Against Natural Language Specifications
Haolin Jin, Huaming Chen
Large language models (LLMs) have become essential tools in software development, widely used for requirements engineering, code generation and review tasks. Software engineers oft…
DistrAttention: An Efficient and Flexible Self-Attention Mechanism on Modern GPUs
Haolin Jin, Mengbai Xiao, Yuan Yuan +4
The Transformer architecture has revolutionized deep learning, delivering the state-of-the-art performance in areas such as natural language processing, computer vision, and time s…
NSW-EPNews: A News-Augmented Benchmark for Electricity Price Forecasting with LLMs
Zhaoge Bi, Linghan Huang, Haolin Jin +2
Electricity price forecasting is a critical component of modern energy-management systems, yet existing approaches heavily rely on numerical histories and ignore contemporaneous te…
The Tower of Babel Revisited: Multilingual Jailbreak Prompts on Closed-Source Large Language Models
Linghan Huang, Haolin Jin, Zhaoge Bi +6
Large language models (LLMs) have seen widespread applications across various domains, yet remain vulnerable to adversarial prompt injections. While most existing research on jailb…
Towards Advancing Code Generation with Large Language Models: A Research Roadmap
Haolin Jin, Huaming Chen, Qinghua Lu +1
Recently, we have witnessed the rapid development of large language models, which have demonstrated excellent capabilities in the downstream task of code generation. However, despi…
RGD: Multi-LLM Based Agent Debugger via Refinement and Generation Guidance
Haolin Jin, Zechao Sun, Huaming Chen
Large Language Models (LLMs) have shown incredible potential in code generation tasks, and recent research in prompt engineering have enhanced LLMs' understanding of textual inform…
AWF: Adaptive Weight Fusion for Enhanced Class Incremental Semantic Segmentation
Zechao Sun, Shuying Piao, Haolin Jin +4
Class Incremental Semantic Segmentation (CISS) aims to mitigate catastrophic forgetting by maintaining a balance between previously learned and newly introduced knowledge. Existing…
From LLMs to LLM-based Agents for Software Engineering: A Survey of Current, Challenges and Future
Haolin Jin, Linghan Huang, Haipeng Cai +3
With the rise of large language models (LLMs), researchers are increasingly exploring their applications in var ious vertical domains, such as software engineering. LLMs have achie…