b'Percy Liang'

research

∙ 08/27/2023

MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records

The ability of large language models (LLMs) to follow natural language i...

0 Scott L. Fleming, et al. ∙

research

∙ 07/28/2023

Robust Distortion-free Watermarks for Language Models

We propose a methodology for planting watermarks in text from an autoreg...

0 Rohith Kuditipudi, et al. ∙

research

∙ 07/12/2023

Ecosystem-level Analysis of Deployed Machine Learning Reveals Homogeneous Outcomes

Machine learning is traditionally studied at the model level: researcher...

0 Connor Toups, et al. ∙

research

∙ 07/06/2023

Lost in the Middle: How Language Models Use Long Contexts

While recent language models have the ability to take long contexts as i...

0 Nelson F. Liu, et al. ∙

research

∙ 06/16/2023

Just One Byte (per gradient): A Note on Low-Bandwidth Decentralized Language Model Finetuning Using Shared Randomness

Language model training in distributed settings is limited by the commun...

0 Eric Zelikman, et al. ∙

research

∙ 06/14/2023

Anticipatory Music Transformer

We introduce anticipation: a method for constructing a controllable gene...

0 John Thickstun, et al. ∙

research

∙ 06/05/2023

Has the Machine Learning Review Process Become More Arbitrary as the Field Has Grown? The NeurIPS 2021 Consistency Experiment

We present the NeurIPS 2021 consistency experiment, a larger-scale varia...

0 Alina Beygelzimer, et al. ∙

research

∙ 05/27/2023

Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models

Language models have been shown to exhibit positive scaling, where perfo...

0 Yuhui Zhang, et al. ∙

research

∙ 05/24/2023

Lexinvariant Language Models

Token embeddings, a mapping from discrete lexical symbols to continuous ...

0 Qian Huang, et al. ∙

research

∙ 05/23/2023

Sophia: A Scalable Stochastic Second-order Optimizer for Language Model Pre-training

Given the massive cost of language model pre-training, a non-trivial imp...

0 Hong Liu, et al. ∙

research

∙ 05/21/2023

PRODIGY: Enabling In-context Learning Over Graphs

In-context learning is the ability of a pretrained model to adapt to nov...

0 Qian Huang, et al. ∙

research

∙ 05/17/2023

DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining

The mixture proportions of pretraining data domains (e.g., Wikipedia, bo...

0 Sang Michael Xie, et al. ∙

research

∙ 05/03/2023

Cheaply Evaluating Inference Efficiency Metrics for Autoregressive Transformer APIs

Large language models (LLMs) power many state-of-the-art systems in natu...

0 Deepak Narayanan, et al. ∙

research

∙ 04/19/2023

Evaluating Verifiability in Generative Search Engines

Generative search engines directly generate responses to user queries, a...

0 Nelson F. Liu, et al. ∙

research

∙ 04/07/2023

Generative Agents: Interactive Simulacra of Human Behavior

Believable proxies of human behavior can empower interactive application...

0 Joon Sung Park, et al. ∙

research

∙ 03/30/2023

Whose Opinions Do Language Models Reflect?

Language models (LMs) are increasingly being used in open-ended contexts...

0 Shibani Santurkar, et al. ∙

research

∙ 03/28/2023

Ecosystem Graphs: The Social Footprint of Foundation Models

Foundation models (e.g. ChatGPT, StableDiffusion) pervasively influence ...

0 Rishi Bommasani, et al. ∙

research

∙ 03/28/2023

Foundation Models and Fair Use

Existing foundation models are trained on copyrighted material. Deployin...

0 Peter Henderson, et al. ∙

research

∙ 03/13/2023

FlexGen: High-Throughput Generative Inference of Large Language Models with a Single GPU

The high computational and memory requirements of large language model (...

0 Ying Sheng, et al. ∙

research

∙ 02/24/2023

Language-Driven Representation Learning for Robotics

Recent work in visual representation learning for robotics demonstrates ...

11 Siddharth Karamcheti, et al. ∙

research

∙ 02/23/2023

Out-of-Domain Robustness via Targeted Augmentations

Models trained on one set of domains often suffer performance drops on u...

0 Irena Gao, et al. ∙

research

∙ 02/06/2023

Data Selection for Language Models via Importance Resampling

Selecting a suitable training dataset is crucial for both general-domain...

0 Sang Michael Xie, et al. ∙

research

∙ 01/31/2023

Benchmarking Large Language Models for News Summarization

Large language models (LLMs) have shown promise for automatic summarizat...

0 Tianyi Zhang, et al. ∙

research

∙ 01/06/2023

"No, to the Right" – Online Language Corrections for Robotic Manipulation via Shared Autonomy

Systems for language-guided human-robot interaction must satisfy two key...

0 Yuchen Cui, et al. ∙

research

∙ 12/28/2022

Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLP

Retrieval-augmented in-context learning has emerged as a powerful approa...

0 Omar Khattab, et al. ∙

research

∙ 12/20/2022

Trustworthy Social Bias Measurement

How do we design measures of social bias that we trust? While prior work...

0 Rishi Bommasani, et al. ∙

research

∙ 12/19/2022

Evaluating Human-Language Model Interaction

Many real-world applications of language models (LMs), such as code auto...

0 Mina Lee, et al. ∙

research

∙ 12/04/2022

Melody transcription via generative pre-training

Despite the central role that melody plays in music perception, it remai...

0 Chris Donahue, et al. ∙

research

∙ 11/25/2022

Picking on the Same Person: Does Algorithmic Monoculture lead to Outcome Homogenization?

As the scope of machine learning broadens, we observe a recurring theme ...

0 Rishi Bommasani, et al. ∙

research

∙ 11/22/2022

Retrieval-Augmented Multimodal Language Modeling

Recent multimodal models such as DALL-E and CM3 have achieved remarkable...

28 Michihiro Yasunaga, et al. ∙

research

∙ 11/22/2022

How do Authors' Perceptions of their Papers Compare with Co-authors' Perceptions and Peer-review Decisions?

How do author perceptions match up to the outcomes of the peer-review pr...

0 Charvi Rastogi, et al. ∙

research

∙ 11/16/2022

Holistic Evaluation of Language Models

Language models (LMs) are becoming the foundation for almost all major l...

21 Percy Liang, et al. ∙

research

∙ 10/27/2022

Truncation Sampling as Language Model Desmoothing

Long samples of text from neural language models can be of poor quality....

0 John Hewitt, et al. ∙

research

∙ 10/27/2022

Contrastive Decoding: Open-ended Text Generation as Optimization

Likelihood, although useful as a training loss, is a poor search objecti...

0 Xiang Lisa Li, et al. ∙

research

∙ 10/20/2022

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts

A common approach to transfer learning under distribution shift is to fi...

6 Yoonho Lee, et al. ∙

research

∙ 10/17/2022

Deep Bidirectional Language-Knowledge Graph Pretraining

Pretraining a language model (LM) on text has been shown to help various...

4 Michihiro Yasunaga, et al. ∙

research

∙ 10/12/2022

Are Sample-Efficient NLP Models More Robust?

Recent work has observed that pre-trained models have higher out-of-dist...

0 Nelson F. Liu, et al. ∙

research

∙ 08/08/2022

Social Simulacra: Creating Populated Prototypes for Social Computing Systems

Social computing prototypes probe the social behaviors that may arise in...

0 Joon Sung Park, et al. ∙

research

∙ 08/01/2022

What Can Transformers Learn In-Context? A Case Study of Simple Function Classes

In-context learning refers to the ability of a model to condition on a p...

0 Shivam Garg, et al. ∙

research

∙ 07/18/2022

Calibrated ensembles can mitigate accuracy tradeoffs under distribution shift

We often see undesirable tradeoffs in robust machine learning where out-...

0 Ananya Kumar, et al. ∙

research

∙ 06/21/2022

Insights into Pre-training via Simpler Synthetic Tasks

Pre-training produces representations that are effective for a wide rang...

0 Yuhuai Wu, et al. ∙

research

∙ 06/02/2022

Decentralized Training of Foundation Models in Heterogeneous Environments

Training foundation models, such as GPT-3 and PaLM, can be extremely exp...

8 Binhang Yuan, et al. ∙

research

∙ 05/27/2022

Diffusion-LM Improves Controllable Text Generation

Controlling the behavior of language models (LMs) without re-training is...

0 Xiang Lisa Li, et al. ∙

research

∙ 04/01/2022

Connect, Not Collapse: Explaining Contrastive Learning for Unsupervised Domain Adaptation

We consider unsupervised domain adaptation (UDA), where labeled data fro...

6 Kendrick Shen, et al. ∙

research

∙ 03/29/2022

LinkBERT: Pretraining Language Models with Document Links

Language model (LM) pretraining can learn various knowledge from text co...

18 Michihiro Yasunaga, et al. ∙

research

∙ 02/21/2022

Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution

When transferring a pretrained model to a downstream task, two popular m...

0 Ananya Kumar, et al. ∙

research

∙ 01/21/2022

GreaseLM: Graph REASoning Enhanced Language Models for Question Answering

Answering complex questions about textual narratives requires reasoning ...

1 Xikun Zhang, et al. ∙

research

∙ 01/18/2022

CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model Capabilities

Large language models (LMs) offer unprecedented language generation capa...

0 Mina Lee, et al. ∙

research

∙ 12/09/2021

Extending the WILDS Benchmark for Unsupervised Adaptation

Machine learning systems deployed in the wild are often trained on a sou...

17 Shiori Sagawa, et al. ∙

research

∙ 11/05/2021

LILA: Language-Informed Latent Actions

We introduce Language-Informed Latent Actions (LILA), a framework for le...

1 Siddharth Karamcheti, et al. ∙

Percy Liang

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