Large Language Models are Efficient Learners of Noise|Robust ...

Large Language Models are Efficient Learners of Noise-Robust ...

Abstract page for arXiv paper 2401.10446: Large Language Models are Efficient Learners of Noise-Robust Speech Recognition.

Large Language Models are Efficient Learners of Noise-Robust ...

Recent advances in large language models (LLMs) have promoted generative error correction (GER) for automatic speech recognition (ASR), ...

Code for paper "Large Language Models are Efficient Learners of ...

This work extends the latest ASR generative error correction (GER) benchmark to noise-robust ASR with a Robust HyPoradise dataset.

Large Language Models are Efficient Learners of Noise-Robust ...

Recent advances in large language models (LLMs) have promoted generative error correction (GER) for automatic speech recognition (ASR), which leverages the ...

LARGE LANGUAGE MODELS ARE EFFICIENT LEARN - OpenReview

Dual-Path Style Learning for End-to-End. Noise-Robust Speech Recognition. In Proc. INTERSPEECH 2023, pp. 2918–2922, 2023d. Yuchen Hu, Ruizhe Li, Chen Chen ...

Large Language Models are Efficient Learners of Noise-Robust ...

The latest work proposes a GER benchmark with ``HyPoradise'' dataset to learn the mapping from ASR N-best hypotheses to ground-truth transcription by efficient ...

Large Language Models are Efficient Learners of Noise-Robust ...

Experimental Results. Applying recent LLMs, including LLaMA-2, LLaMA, and Falcon, the proposed approach termed RobustGER is demonstrated to ...

Large Language Models are Efficient Learners of Noise-Robust ...

This work proposes to extract a language-space noise embedding from the N-best list to represent the noise conditions of source speech, ...

Noise-Robust Fine-Tuning of Pretrained Language Models via ...

the power of Large LAnguage Models (LLMs) for. Fine-Tuning PLMs. We ... Instance-dependent label- noise learning under a structural causal model.

Large Language Models Can be Lazy Learners: Analyze Shortcuts ...

This approach allows us to equip LLMs with two types of knowledge during in-context learning: non-robust knowledge and robust knowledge (Ilyas.

Why Is Prompt Tuning for Vision-Language Models Robust to Noisy ...

Analysis of Prompt Tuning with Label Noise. Methods based on prompt tuning for CLIP [27] have been shown to be effective in few-shot learning [50, 49].

[D] Why are so many tokens needed to train large language models?

develop a method to separate knowledge retention and language pattern modeling. Think about learning the state capitals. A person quickly learns ...

Evaluating large language models in analysing classroom dialogue

This study explores the use of Large Language Models (LLMs), specifically GPT-4, in analysing classroom dialogue—a key task for teaching ...

Are large language models like GPT a dead end? - Reddit

As a layman, my understanding of how large language models like GPT roughly work is that based on a large amount of training data (made by ...

(PDF) Large Language Models Are Strong Audio-Visual Speech ...

Large Language Models Are Strong Audio-Visual Speech Recognition Learners · Abstract and Figures · Citations (0) · References (49) · Recommended ...

What is a Large Language Model? LLMs Explained - Aisera

Limitations and Challenges of Large Language Models · – Biased Output · – AI Hallucination · – Ethical Concerns · – Computational Requirements · – Robust Evaluation ...

Teaching Large Language Models to Reason with Reinforcement ...

Today we're joined by Alex Havrilla, a PhD student at Georgia Tech, to discuss "Teaching Large Language Models to Reason with Reinforcement ...

Fine-tuning large language models (LLMs) in 2024 - SuperAnnotate

This approach is both computationally efficient and time-saving. Additionally, pre-training captures general language understanding, allowing ...

MIT researchers make language models scalable self-learners

The scientists used a natural language-based logical inference dataset to create smaller language models that outperformed much larger counterparts.

Large language model - Wikipedia

A large language model (LLM) is a type of computational model designed for natural language processing tasks such as language generation. As language models ...