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Qi Lin

4 accepted papers

2025

Bit-Flip Error Resilience in LLMs: A Comprehensive Analysis and Defense Framework

EMNLP 2025

Bit-flip errors (BFEs) are hardware faults where individual bits in memory or processing units are unintentionally flipped. These errors pose a significant threat to neural network reliability because even small changes in model parameters can lead to large shifts in outputs. Large language models (

2025

Data with High and Consistent Preference Difference Are Better for Reward Model

AAAI 2025technical

Reinforcement Learning from Human Feedback (RLHF) is a commonly used alignment method for Large Language Models (LLMs). This method relies on a reward model trained on a preference dataset to provide scalar rewards. However, the human-annotated preference data is often sparse, noisy, and costly to o…

2025

V-VAE: A Variational Auto Encoding Framework Towards Fine-Grained Control over Human-Like Chat

EMNLP 2025

With the continued proliferation of Large Language Model (LLM) based chatbots, there is a growing demand for generating responses that are not only linguistically fluent but also consistently aligned with persona-specific traits in conversations. However, existing role-play and persona-based chat ap

Cited by 0SourcePDFScholar
2022

Colorization for In Situ Marine Plankton Images

ECCV 2022poster

"Underwater imaging with red-NIR light illumination can avoid phototropic aggregation-induced observational deviation of marine plankton abundance under white light illumination, but this will lead to the loss of critical color information in the collected grayscale images, which is non-preferable t…

Cited by 2SourcePDFScholar