Semanlink - ML: evaluation AND NLP

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ML: evaluation AND NLP

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22 Documents

On the Surprising Behavior of Distance Metrics in High Dimensional Space (Aggarwal 2001)

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2024-03-03 About

Jerry Liu sur X : "how do you get a good retrieval dataset w/o spending a ton of money on human labels? Answer: use LLMs"

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2023-08-30 About

Yann Dubois sur Twitter : "Developing chat LLMs is hard without an automated way to measure improvements 🔥It just became easier with AlpacaEval..."

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2023-06-08 About

Lex-GPT

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2023-05-27 About

Auto-Evaluator - autoevaluator.langchain.com

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2023-05-27 About

openai/evals: Evals is a framework for evaluating LLMs and LLM systems, and an open-source registry of benchmarks.

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2023-05-04 About

[2304.09848] Evaluating Verifiability in Generative Search Engines

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2023-04-23 About

Auto-Eval of Question-Answering Tasks

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2023-04-17 About

Jerry Liu sur Twitter : "To evaluate retrieval-augmented LLM’s, we can compare the query/response/source context to see if they match. We just added this to @gpt_index..."

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2023-04-11 About

[2211.09110] Holistic Evaluation of Language Models

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2022-12-06 About

Evaluation Measures in Information Retrieval | Pinecone

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2022-06-29 About

huggingface/evaluate: A library for easily evaluating machine learning models and datasets.

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2022-06-05 About

(((ل()(ل() 'yoav))))👾 sur Twitter : "my two cents on why NLP as a field is focusing on the ML-ish / algorithmic / leaderboard-ish aspects (incl., now, LLMs) and not on the underlying language phenomena: it is just so much easier, on so many levels."

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2021-08-30 About

[2004.14958] A Call for More Rigor in Unsupervised Cross-lingual Learning

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2020-05-02 About

Evaluation of sentence embeddings in downstream and linguistic probing tasks

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2018-06-27 About

[1806.06259] Evaluation of sentence embeddings in downstream and linguistic probing tasks

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2018-06-19 About

Comparing Sentence Similarity Methods

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2018-05-25 About

Improving Word Embedding Compositionality using Lexicographic Definitions

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2018-05-10 About

Improving the Compositionality of Word Embeddings (2017)

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(MS thesis, a [paper at TheWebConf 2018](/doc/?uri=https%3A%2F%2Fdoi.org%2F10.1145%2F3178876.3186007))

> This thesis explores a method to find better encodings of meaning a computer can work with. We specifically want to combine encodings of word meanings in such a way that a good encoding of their joint meaning is created. The act of combining multiple representations of meaning into a new representation of meaning is called semantic composition.

Analysis of four word embeddings (Word2Vec, GloVe, fastText and Paragram)  in terms of their semantic compositionality. A method to tune these embeddings towards better compositionality, using a simple neural network architecture with definitions and lemmas from WordNet.

> Since dictionary definitions are semantically similar to their associated lemmas, they are the ideal candidate for our tuning method, as well as evaluating for compositionality. Our architecture allows for the embeddings to be composed using simple arithmetic operations, which makes these embeddings specifically suitable for production applications such as web search and data mining. We also explore more elaborate and involved compositional models, such as recurrent composition and convolutional composition.

2018-02-13 About

Towards a Seamless Integration of Word Senses into Downstream NLP Applications (2017)

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2017-10-21 About

An overview of word embeddings and their connection to distributional semantic models - AYLIEN (2016)

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2017-07-20 About

Don’t count, predict! A systematic comparison of context-counting vs. context-predicting semantic vectors (2014)

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2017-05-18 About