Lost in the Middle: How Language Models Use Long Contexts paper page: https://
huggingface.co/papers/2307.03
172
… While recent language models have the ability to take long contexts as input, relatively little is known about how well the language models use longer context. We analyze language
MACHINE LEARNING
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Language Models Using Long Contexts: Analysis and Findings
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Whisper-AT: Noise-Robust Speech Recognition and Audio Event Tagging
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Whisper-AT: Noise-Robust Automatic Speech Recognizers are Also Strong General Audio Event Taggers paper page: https://
huggingface.co/papers/2307.03
183
… In this paper, we focus on Whisper, a recent automatic speech recognition model trained with a massive 680k hour labeled speech corpus recorded -

VideoGLUE: Evaluating Foundation Models Video Understanding Capabilities
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GLUE: General Understanding Evaluation of Foundation Models paper page: https://
huggingface.co/papers/2307.03
166
… We evaluate existing foundation models video understanding capabilities using a carefully designed experiment protocol consisting of three hallmark tasks (action -

LongLLaMA: Large Language Model Supporting 256k Token Contexts
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TLDR LongLLaMA, a large language model capable of handling long contexts of 256k tokens or even more https://
huggingface.co/syzymon/long_l
lama_3b
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Focused Transformer: Contrastive Training for Context Scaling
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Focused Transformer: Contrastive Training for Context Scaling paper page: https://
huggingface.co/papers/2307.03
170
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model: https://
huggingface.co/syzymon/long_l
lama_3b
… Large language models have an exceptional capability to incorporate new information in a contextual manner. However, the full potential of such an -

Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts
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Training Models to Generate, Recognize, and Reframe Unhelpful Thoughts paper page: https://
huggingface.co/papers/2307.02
768
… Many cognitive approaches to well-being, such as recognizing and reframing unhelpful thoughts, have received considerable empirical support over the past decades, yet -

SkipDecode: Efficient LLM Inference with Autoregressive Skip Decoding
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SkipDecode: Autoregressive Skip Decoding with Batching and Caching for Efficient LLM Inference paper page: https://
huggingface.co/papers/2307.02
628
… Autoregressive large language models (LLMs) have made remarkable progress in various natural language generation tasks. However, they incur high -

mPLUG-DocOwl: Multimodal LLM for Document Understanding
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mPLUG-DocOwl: Modularized Multimodal Large Language Model for Document Understanding paper page: https://
huggingface.co/papers/2307.02
499
… Document understanding refers to automatically extract, analyze and comprehend information from various types of digital documents, such as a web page. -

Changelog: Updates for AI and Machine Learning
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Changelog
https://bit.ly/448H1YJ #AI #MachineLearning #DeepLearning #LLMs #DataScience