Ian Tenney | DeepAI

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∙ 03/14/2023

Simfluence: Modeling the Influence of Individual Training Examples by Simulating Training Runs

Training data attribution (TDA) methods offer to trace a model's predict...

0 Kelvin Guu, et al. ∙

∙ 05/23/2022

Tracing Knowledge in Language Models Back to the Training Data

Neural language models (LMs) have been shown to memorize a great deal of...

0 Ekin Akyürek, et al. ∙

∙ 10/14/2021

Retrieval-guided Counterfactual Generation for QA

Deep NLP models have been shown to learn spurious correlations, leaving ...

0 Bhargavi Paranjape, et al. ∙

∙ 06/30/2021

The MultiBERTs: BERT Reproductions for Robustness Analysis

Experiments with pretrained models such as BERT are often based on a sin...

0 Thibault Sellam, et al. ∙

∙ 10/12/2020

Measuring and Reducing Gendered Correlations in Pre-trained Models

Pre-trained models have revolutionized natural language understanding. H...

1 Kellie Webster, et al. ∙

∙ 10/11/2020

Do Language Embeddings Capture Scales?

Pretrained Language Models (LMs) have been shown to possess significant ...

0 Xikun Zhang, et al. ∙

∙ 08/12/2020

The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models

We present the Language Interpretability Tool (LIT), an open-source plat...

0 Ian Tenney, et al. ∙

∙ 04/29/2020

Asking without Telling: Exploring Latent Ontologies in Contextual Representations

The success of pretrained contextual encoders, such as ELMo and BERT, ha...

0 Julian Michael, et al. ∙

∙ 04/29/2020

What Happens To BERT Embeddings During Fine-tuning?

While there has been much recent work studying how linguistic informatio...

0 Amil Merchant, et al. ∙

∙ 03/04/2020

jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models

We introduce jiant, an open source toolkit for conducting multitask and ...

0 Yada Pruksachatkun, et al. ∙

∙ 05/15/2019

What do you learn from context? Probing for sentence structure in contextualized word representations

Contextualized representation models such as ELMo (Peters et al., 2018a)...

0 Ian Tenney, et al. ∙

∙ 05/15/2019

BERT Rediscovers the Classical NLP Pipeline

Pre-trained text encoders have rapidly advanced the state of the art on ...

0 Ian Tenney, et al. ∙

∙ 04/25/2019

Probing What Different NLP Tasks Teach Machines about Function Word Comprehension

We introduce a set of nine challenge tasks that test for the understandi...

0 Najoung Kim, et al. ∙

∙ 12/28/2018

Looking for ELMo's friends: Sentence-Level Pretraining Beyond Language Modeling

Work on the problem of contextualized word representation -- the develop...

0 Samuel R. Bowman, et al. ∙

∙ 08/28/2018

WikiAtomicEdits: A Multilingual Corpus of Wikipedia Edits for Modeling Language and Discourse

We release a corpus of 43 million atomic edits across 8 languages. These...

0 Manaal Faruqui, et al. ∙

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