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Qinhong Lin

2 accepted papers

2025

Approximated Variational Bayesian Inverse Reinforcement Learning for Large Language Model Alignment

AAAI 2025technical

The alignment of large language models (LLMs) is crucial for generating helpful and harmless content. Existing approaches leverage preference-based human feedback data to learn the reward function and align the LLM with the feedback data. However, these approaches focus on modeling the reward differ…

Cited by 0SourcePDFScholar
2025

Semantic Contribution-Aware Adaptive Retrieval for Black-Box Models

EMNLP 2025

Retrieval-Augmented Generation (RAG) plays a critical role in mitigating hallucinations and improving factual accuracy for Large Language Models (LLMs). While dynamic retrieval techniques aim to determine retrieval timing and content based on model intrinsic needs, existing approaches struggle to ge