Ethan Perez | DeepAI

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∙ 08/07/2023

Studying Large Language Model Generalization with Influence Functions

When trying to gain better visibility into a machine learning model in o...

0 Roger Grosse, et al. ∙

∙ 06/15/2023

Inverse Scaling: When Bigger Isn't Better

Work on scaling laws has found that large language models (LMs) show pre...

0 Ian R. McKenzie, et al. ∙

∙ 05/07/2023

Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting

Large Language Models (LLMs) can achieve strong performance on many task...

0 Miles Turpin, et al. ∙

∙ 03/28/2023

Training Language Models with Language Feedback at Scale

Pretrained language models often generate outputs that are not in line w...

1 Jérémy Scheurer, et al. ∙

∙ 03/28/2023

Improving Code Generation by Training with Natural Language Feedback

The potential for pre-trained large language models (LLMs) to use natura...

1 Angelica Chen, et al. ∙

∙ 02/16/2023

Pretraining Language Models with Human Preferences

Language models (LMs) are pretrained to imitate internet text, including...

0 Tomasz Korbak, et al. ∙

∙ 02/15/2023

The Capacity for Moral Self-Correction in Large Language Models

We test the hypothesis that language models trained with reinforcement l...

0 Deep Ganguli, et al. ∙

∙ 12/15/2022

Constitutional AI: Harmlessness from AI Feedback

As AI systems become more capable, we would like to enlist their help to...

0 Yuntao Bai, et al. ∙

∙ 11/04/2022

Measuring Progress on Scalable Oversight for Large Language Models

Developing safe and useful general-purpose AI systems will require us to...

0 Samuel R. Bowman, et al. ∙

∙ 08/23/2022

Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned

We describe our early efforts to red team language models in order to si...

0 Deep Ganguli, et al. ∙

∙ 08/01/2022

Few-shot Adaptation Works with UnpredicTable Data

Prior work on language models (LMs) shows that training on a large numbe...

0 Jun Shern Chan, et al. ∙

∙ 07/11/2022

Language Models (Mostly) Know What They Know

We study whether language models can evaluate the validity of their own ...

12 Saurav Kadavath, et al. ∙

∙ 05/23/2022

RL with KL penalties is better viewed as Bayesian inference

Reinforcement learning (RL) is frequently employed in fine-tuning large ...

0 Tomasz Korbak, et al. ∙

∙ 04/29/2022

Training Language Models with Natural Language Feedback

Pretrained language models often do not perform tasks in ways that are i...

7 Jérémy Scheurer, et al. ∙

∙ 04/11/2022

Single-Turn Debate Does Not Help Humans Answer Hard Reading-Comprehension Questions

Current QA systems can generate reasonable-sounding yet false answers wi...

0 Alicia Parrish, et al. ∙

∙ 02/07/2022

Red Teaming Language Models with Language Models

Language Models (LMs) often cannot be deployed because of their potentia...

0 Ethan Perez, et al. ∙

∙ 05/24/2021

True Few-Shot Learning with Language Models

Pretrained language models (LMs) perform well on many tasks even when le...

12 Ethan Perez, et al. ∙

∙ 04/18/2021

Case-based Reasoning for Natural Language Queries over Knowledge Bases

It is often challenging for a system to solve a new complex problem from...

21 Rajarshi Das, et al. ∙

∙ 03/05/2021

Rissanen Data Analysis: Examining Dataset Characteristics via Description Length

We introduce a method to determine if a certain capability helps to achi...

5 Ethan Perez, et al. ∙

∙ 05/22/2020

Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks

Large pre-trained language models have been shown to store factual knowl...

0 Patrick Lewis, et al. ∙

∙ 02/22/2020

Unsupervised Question Decomposition for Question Answering

We aim to improve question answering (QA) by decomposing hard questions ...

14 Ethan Perez, et al. ∙

∙ 09/12/2019

Finding Generalizable Evidence by Learning to Convince Q A Models

We propose a system that finds the strongest supporting evidence for a g...

15 Ethan Perez, et al. ∙

∙ 07/22/2019

ELI5: Long Form Question Answering

We introduce the first large-scale corpus for long-form question answeri...

0 Angela Fan, et al. ∙

∙ 08/03/2018

Visual Reasoning with Multi-hop Feature Modulation

Recent breakthroughs in computer vision and natural language processing ...

0 Florian Strub, et al. ∙

∙ 11/29/2017

HoME: a Household Multimodal Environment

We introduce HoME: a Household Multimodal Environment for artificial age...

0 Simon Brodeur, et al. ∙

∙ 09/22/2017

FiLM: Visual Reasoning with a General Conditioning Layer

We introduce a general-purpose conditioning method for neural networks c...

0 Ethan Perez, et al. ∙

∙ 07/10/2017

Learning Visual Reasoning Without Strong Priors

Achieving artificial visual reasoning - the ability to answer image-rela...

0 Ethan Perez, et al. ∙

∙ 12/06/2016

Semi-Supervised Learning with the Deep Rendering Mixture Model

Semi-supervised learning algorithms reduce the high cost of acquiring la...

0 Tan Nguyen, et al. ∙

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