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JD Tech
JD Tech
Jul 22, 2024 · Artificial Intelligence

Task‑Aware Decoding (TaD): A Plug‑and‑Play Method to Mitigate Hallucinations in Large Language Models

This article presents Task‑aware Decoding (TaD), a plug‑and‑play technique introduced by JD Tech and Tsinghua University and accepted at IJCAI 2024, which reduces intrinsic hallucinations in large language models by comparing pre‑ and post‑fine‑tuning outputs, and demonstrates its effectiveness combined with Retrieval‑Augmented Generation across various tasks.

LLMRetrieval-Augmented GenerationTask-aware Decoding
0 likes · 18 min read
Task‑Aware Decoding (TaD): A Plug‑and‑Play Method to Mitigate Hallucinations in Large Language Models
JD Tech Talk
JD Tech Talk
Jul 16, 2024 · Artificial Intelligence

Task‑Aware Decoding (TaD): A Plug‑and‑Play Method to Mitigate Hallucinations in Large Language Models

TaD, a task‑aware decoding technique jointly developed by JD.com and Tsinghua University and presented at IJCAI 2024, leverages differences between pre‑ and post‑fine‑tuned LLM outputs to construct knowledge vectors, significantly reducing hallucinations across various models, tasks, and data‑scarce scenarios, especially when combined with RAG.

AILLMRAG
0 likes · 18 min read
Task‑Aware Decoding (TaD): A Plug‑and‑Play Method to Mitigate Hallucinations in Large Language Models
JD Retail Technology
JD Retail Technology
Jul 15, 2024 · Artificial Intelligence

Can Task‑Aware Decoding Tame LLM Hallucinations? Insights from IJCAI 2024

This article reviews the IJCAI 2024‑presented Task‑aware Decoding (TaD) technique, explains how it mitigates large‑language‑model hallucinations when combined with Retrieval‑augmented Generation, and details experimental results, practical deployments, and future research directions.

AI researchHallucination MitigationIJCAI2024
0 likes · 19 min read
Can Task‑Aware Decoding Tame LLM Hallucinations? Insights from IJCAI 2024