Language Models are Changing AI: The Need for Holistic Evaluation. New benchmarking method, Holistic Evaluation of Language Models (HELM) has been developed at the Center for Research on Foundation Models to help provide transparency in LMs. @RishiBommasani
, @PercyLiang
, Tony Lee
RESEARCH
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HELM: Holistic Evaluation Method for Language Models
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Explainable Artificial Intelligence XAI for Engineers
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Explainable Artificial Intelligence (XAI) for AI & ML Engineers: This article was published as a part of the Data Science Blogathon. Introduction Hello AI&ML Engineers, as you all know, Artificial Intelligence (AI) and Machine Learning Engineering are… https://
analyticsvidhya.com/blog/2022/10/e
xplainable-artificial-intelligence-xai-for-ai-ml-engineers/?utm_source=dlvr.it&utm_medium=twitter
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Teaching Algorithmic Reasoning to LLMs via In-context Learning
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Teaching Algorithmic Reasoning via In-context Learning. A four-stage approach to teaching algorithmic reasoning to LLMs is identified and studied in this work by @oh_that_hat
, @Azade_Na
, @Hugo_Larochelle
, Aaron Courville, @BNeyshabur
, @HanieSedghi -
Fast DistilBERT Pipeline for CPU Inference Optimization
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Fast DistilBERT on CPUs. @HaihaoShen
, @ZafrirOfir
, Bo Dong, Hengyu Meng, Xinyu Ye, Zhe Wang, Yi Ding, Hanwen Chang, Guy Boudoukh, @MosheWasserblat propose a new pipeline for creating and running Fast Transformer models on CPUs -
Intermediate Models Value Through Transfer Learning Fine-tuning
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Where to start? Analyzing the potential value of intermediate models. By finetuning a model on a source dataset, one may have a better starting point when finetuning a target dataset. @LChoshen
, Elad Venezian, Shachar Don-Yehia, @NoamSlonim
, @YoavKatz -
LLMs Struggle Learning Long-Tail Knowledge From Training Data
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Large Language Models Struggle to Learn Long-Tail Knowledge. @kandpal_nikhil
, @HaikangDeng
, Adam Roberts, @Eric_Wallace_
, @ColinRaffel examine the relationship between their pre-training datasets and their knowledge memorized. -
Top NLP Research Papers November 2022
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If you work in #NLP, it's important to keep up to date with the latest research. In this post, we look at some of the top papers on NLP that were published in November 2022 https://
txt.cohere.ai/top-nlp-papers
-november-2022/
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Geoff Hinton: Future Computing is Analog, Mortal Computation
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AI pioneer Geoff Hinton says the future of computing is analog, something I’ve long believed. I think he’s right. And, the term mortal computation is a great moniker. // @geoffreyhinton // #computing #AI #deeplearning #mortalcomputation // @NeurIPSConf
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Initial Fine-Tuning Approach: Breaking Books into Chunks and Generating Questions
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initial approach: oh this seems not too bad, I read this doc https://
beta.openai.com/docs/guides/fi
ne-tuning
… and was like yeah I can just break up the authors' books into chunks and generate some simple questions for each chunk and then use that to fine-tune the model -
Fine-tuning models is easy but data preparation remains challenging
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it was easy to fine-tune the models (sorta, gathering and cleaning the data sucked and it doesn't look like there is any easy automatic process to do this yet in terms of a simple online tool)