Evaluation of Context|Aware Language Models and Experts for ...

Retrieval-Augmented Large Language Model for Ophthalmology

This quality improvement study discusses the challenges of knowledge inaccuracies and data privacy issues when using large language models ...

Quality of Answers of Generative Large Language Models Versus ...

Quality of Answers of Generative Large Language Models Versus Peer Users for Interpreting Laboratory Test Results for Lay Patients: Evaluation ...

An Empirical Evaluation of Prompting Strategies for Large Language ...

Background: Large language models (LLMs) have shown remarkable capabilities in natural language processing (NLP), especially in domains ...

Long-Context Understanding | Papers With Code

With the advancement of large language models (LLMs) and the expansion of their context windows, existing long-context benchmarks fall short in effectively ...

How long-context LLMs are changing | Yennie Jun posted on the topic

Large language models' context windows have been increasing at an exponential rate. In 2018, language models like BERT, T5, and GPT-1 could ...

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts

Wic: 10, 000 example pairs for evaluating context-sensitive representa- tions. ArXiv, abs/1808.09121, 2018. Radford, A., Wu, J., Child, R ...

Introducing Llama 3.1: Our most capable models to date - AI at Meta

As expected per scaling laws for language models, our new flagship model outperforms smaller models trained using the same procedure. We also ...

hallenges in Language Model Evaluations: Insights and Tips

Evaluating large language models (LLMs) requires multidimensional strategies to assess coherence, accuracy, and fluency. Explore key benchmarks, ...

A survey of context in neural machine translation and its evaluation

Furthermore, we also discuss recent experiments in the field as they relate to the use of large language models in translation and evaluation.

Large Language Model Evaluation: 5 Methods - Research AIMultiple

Consider an enterprise that needs to choose between multiple models for its base enterprise generative model. These LLMs need to be evaluated to ...

What Is NLP (Natural Language Processing)? - IBM

Self-supervised learning (SSL) in particular is useful for supporting NLP because NLP requires large amounts of labeled data to train AI models.

Accepted Findings Papers - ACL 2024

... Models on CFLUE - A Chinese Financial Language Understanding Evaluation ... Concept-aware Data Construction Improves In-context Learning of Language Models

Evaluating Large Language Models: A Complete Guide - SingleStore

It has become critical for organizations to adhere to the safe, secure and responsible use of LLMs for AI. It is highly recommended to evaluate ...

Evaluating Large Language Models: Methods, Best Practices & Tools

Introduced by Kishore Papineni and his team in 2002, BLEU was originally designed for machine translation evaluation. It has become a primary ...

To Sentences and Beyond! Paving the way for Context-Aware ...

... evaluation dataset that specifically addresses the translation ... Luca Soldaini - OLMo: Accelerating the Science of Open Language Models.

Bias and Fairness in Large Language Models: A Survey

Our first taxonomy of metrics for bias evaluation disambiguates the relationship between metrics and evaluation datasets, and organizes metrics by the different ...

Daily Papers - Hugging Face

by AK and the research community · Multimodal Needle in a Haystack: Benchmarking Long-Context Capability of Multimodal Large Language Models.

Evaluating large language models on a highly-specialized topic ...

Due to the nature of transformer-based LLMs predicting the next word based on the prior context, it has been shown that the accuracy of responses can be ...

In-Context Impersonation Reveals Large Language Models ...

Second, we evaluate the effect of domain expert impersonation on natural language reasoning tasks (yellow). Third, we study the usefulness of descriptions ...

Introducing the next generation of Claude - Anthropic

A new standard for intelligence. Opus, our most intelligent model, outperforms its peers on most of the common evaluation benchmarks for AI ...