ICML2024 | BestHub

AntTech

Aug 6, 2024 · Artificial Intelligence

Trustworthy Alignment of Retrieval‑Augmented Large Language Models via Reinforcement Learning

The article explains how recent research tackles large language model hallucinations by combining retrieval‑augmented generation with reinforcement learning, achieving significant accuracy and reliability gains and paving the way for safe AI deployment in critical sectors such as finance and healthcare.

ICML2024Retrieval-Augmented Generationhallucination

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Trustworthy Alignment of Retrieval‑Augmented Large Language Models via Reinforcement Learning

AntTech

Jul 23, 2024 · Artificial Intelligence

Ant Group’s 11 Papers Accepted at ICML 2024 Cover AI Efficiency, Security, Multimodal Learning, and More

At ICML 2024 in Vienna, Ant Group had eleven papers accepted, spanning topics such as quantization-aware secure inference for transformers, multimodal contrastive captioners, self-cognitive denoising with noisy labels, directed graph embedding, GAN improvement via score matching, and trustworthy alignment of retrieval-augmented large language models.

AI securityAnt GroupICML2024

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Ant Group’s 11 Papers Accepted at ICML 2024 Cover AI Efficiency, Security, Multimodal Learning, and More