b'Dan Klein'

research

∙ 08/21/2023

Can Language Models Learn to Listen?

We present a framework for generating appropriate facial responses from ...

0 Evonne Ng, et al. ∙

research

∙ 07/31/2023

Learning to Model the World with Language

To interact with humans in the world, agents need to understand the dive...

0 Jessy Lin, et al. ∙

research

∙ 07/24/2023

RLCD: Reinforcement Learning from Contrast Distillation for Language Model Alignment

We propose Reinforcement Learning from Contrast Distillation (RLCD), a m...

0 Kevin Yang, et al. ∙

research

∙ 07/06/2023

PREADD: Prefix-Adaptive Decoding for Controlled Text Generation

We propose Prefix-Adaptive Decoding (PREADD), a flexible method for cont...

0 Jonathan Pei, et al. ∙

research

∙ 06/08/2023

Modular Visual Question Answering via Code Generation

We present a framework that formulates visual question answering as modu...

6 Sanjay Subramanian, et al. ∙

research

∙ 05/24/2023

Decomposing Complex Queries for Tip-of-the-tongue Retrieval

When re-finding items, users who forget or are uncertain about identifyi...

5 Kevin Lin, et al. ∙

research

∙ 05/24/2023

Ghostbuster: Detecting Text Ghostwritten by Large Language Models

We introduce Ghostbuster, a state-of-the-art system for detecting AI-gen...

0 Vivek Verma, et al. ∙

research

∙ 05/24/2023

Centering the Margins: Outlier-Based Identification of Harmed Populations in Toxicity Detection

A standard method for measuring the impacts of AI on marginalized commun...

0 Vyoma Raman, et al. ∙

research

∙ 05/20/2023

Revisiting Entropy Rate Constancy in Text

The uniform information density (UID) hypothesis states that humans tend...

0 Vivek Verma, et al. ∙

research

∙ 05/11/2023

When the Majority is Wrong: Leveraging Annotator Disagreement for Subjective Tasks

Though majority vote among annotators is typically used for ground truth...

0 Eve Fleisig, et al. ∙

research

∙ 05/01/2023

Poisoning Language Models During Instruction Tuning

Instruction-tuned LMs such as ChatGPT, FLAN, and InstructGPT are finetun...

0 Alexander Wan, et al. ∙

research

∙ 02/28/2023

Goal Driven Discovery of Distributional Differences via Language Descriptions

Mining large corpora can generate useful discoveries but is time-consumi...

0 Ruiqi Zhong, et al. ∙

research

∙ 12/22/2022

Towards an Ontology-Driven Approach for Process-Aware Risk Propagation

The rapid development of cyber-physical systems creates an increasing de...

0 Gal Engelberg, et al. ∙

research

∙ 12/20/2022

DOC: Improving Long Story Coherence With Detailed Outline Control

We propose the Detailed Outline Control (DOC) framework for improving lo...

5 Kevin Yang, et al. ∙

research

∙ 12/07/2022

Discovering Latent Knowledge in Language Models Without Supervision

Existing techniques for training language models can be misaligned with ...

0 Collin Burns, et al. ∙

research

∙ 11/16/2022

Neural Unsupervised Reconstruction of Protolanguage Word Forms

We present a state-of-the-art neural approach to the unsupervised recons...

0 Andre He, et al. ∙

research

∙ 10/13/2022

Re3: Generating Longer Stories With Recursive Reprompting and Revision

We consider the problem of automatically generating longer stories of ov...

4 Kevin Yang, et al. ∙

research

∙ 09/30/2022

Learning by Distilling Context

Language models significantly benefit from context tokens, such as promp...

8 Charlie Snell, et al. ∙

research

∙ 09/16/2022

The Whole Truth and Nothing But the Truth: Faithful and Controllable Dialogue Response Generation with Dataflow Transduction and Constrained Decoding

In a real-world dialogue system, generated responses must satisfy severa...

10 Hao Fang, et al. ∙

research

∙ 05/25/2022

Active Programming by Example with a Natural Language Prior

We introduce APEL, a new framework that enables non-programmers to indir...

0 Ruiqi Zhong, et al. ∙

research

∙ 05/19/2022

Voxel-informed Language Grounding

Natural language applied to natural 2D images describes a fundamentally ...

1 Rodolfo Corona, et al. ∙

research

∙ 05/19/2022

Automated Crossword Solving

We present the Berkeley Crossword Solver, a state-of-the-art approach fo...

17 Eric Wallace, et al. ∙

research

∙ 04/15/2022

Understanding Game-Playing Agents with Natural Language Annotations

We present a new dataset containing 10K human-annotated games of Go and ...

4 Nicholas Tomlin, et al. ∙

research

∙ 04/05/2022

Inferring Rewards from Language in Context

In classic instruction following, language like "I'd like the JetBlue fl...

2 Jessy Lin, et al. ∙

research

∙ 01/28/2022

Summarizing Differences between Text Distributions with Natural Language

How do two distributions of texts differ? Humans are slow at answering t...

16 Ruiqi Zhong, et al. ∙

research

∙ 09/10/2021

Reference-Centric Models for Grounded Collaborative Dialogue

We present a grounded neural dialogue model that successfully collaborat...

2 Daniel Fried, et al. ∙

research

∙ 06/19/2021

Learning Space Partitions for Path Planning

Path planning, the problem of efficiently discovering high-reward trajec...

5 Kevin Yang, et al. ∙

research

∙ 06/03/2021

An Improved Model for Voicing Silent Speech

In this paper, we present an improved model for voicing silent speech, w...

13 David Gaddy, et al. ∙

research

∙ 05/13/2021

Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level

Larger language models have higher accuracy on average, but are they bet...

14 Ruiqi Zhong, et al. ∙

research

∙ 04/18/2021

Constrained Language Models Yield Few-Shot Semantic Parsers

We explore the use of large pretrained language models as few-shot seman...

9 Richard Shin, et al. ∙

research

∙ 04/13/2021

Detoxifying Language Models Risks Marginalizing Minority Voices

Language models (LMs) must be both safe and equitable to be responsibly ...

12 Albert Xu, et al. ∙

research

∙ 04/12/2021

FUDGE: Controlled Text Generation With Future Discriminators

We propose Future Discriminators for Generation (FUDGE), a flexible and ...

18 Kevin Yang, et al. ∙

research

∙ 04/10/2021

Meta-tuning Language Models to Answer Prompts Better

Large pretrained language models like GPT-3 have acquired a surprising a...

9 Ruiqi Zhong, et al. ∙

research

∙ 03/13/2021

Approximating How Single Head Attention Learns

Why do models often attend to salient words, and how does this evolve th...

4 Charlie Snell, et al. ∙

research

∙ 02/19/2021

Calibrate Before Use: Improving Few-Shot Performance of Language Models

GPT-3 can perform numerous tasks when provided a natural language prompt...

6 Tony Z. Zhao, et al. ∙

research

∙ 10/24/2020

Modularity Improves Out-of-Domain Instruction Following

We propose a modular architecture for following natural language instruc...

3 Rodolfo Corona, et al. ∙

research

∙ 10/07/2020

Unsupervised Parsing via Constituency Tests

We propose a method for unsupervised parsing based on the linguistic not...

0 Steven Cao, et al. ∙

research

∙ 10/06/2020

Digital Voicing of Silent Speech

In this paper, we consider the task of digitally voicing silent speech, ...

0 David Gaddy, et al. ∙

research

∙ 10/06/2020

Semantic Evaluation for Text-to-SQL with Distilled Test Suites

We propose test suite accuracy to approximate semantic accuracy for Text...

0 Ruiqi Zhong, et al. ∙

research

∙ 10/05/2020

A Streaming Approach For Efficient Batched Beam Search

We propose an efficient batching strategy for variable-length decoding o...

0 Kevin Yang, et al. ∙

research

∙ 09/24/2020

Task-Oriented Dialogue as Dataflow Synthesis

We describe an approach to task-oriented dialogue in which dialogue stat...

0 Jacob Andreas, et al. ∙

research

∙ 05/12/2020

Semantic Scaffolds for Pseudocode-to-Code Generation

We propose a method for program generation based on semantic scaffolds, ...

0 Ruiqi Zhong, et al. ∙

research

∙ 02/26/2020

Train Large, Then Compress: Rethinking Model Size for Efficient Training and Inference of Transformers

Since hardware resources are limited, the objective of training deep lea...

0 Zhuohan Li, et al. ∙

research

∙ 02/10/2020

Multilingual Alignment of Contextual Word Representations

We propose procedures for evaluating and strengthening contextual embedd...

0 Steven Cao, et al. ∙

research

∙ 10/02/2019

A Deep Factorization of Style and Structure in Fonts

We propose a deep factorization model for typographic analysis that dise...

28 Akshay Srivatsan, et al. ∙

research

∙ 07/23/2019

Pre-Learning Environment Representations for Data-Efficient Neural Instruction Following

We consider the problem of learning to map from natural language instruc...

2 David Gaddy, et al. ∙

research

∙ 07/09/2019

Cross-Domain Generalization of Neural Constituency Parsers

Neural parsers obtain state-of-the-art results on benchmark treebanks fo...

0 Daniel Fried, et al. ∙

research

∙ 06/02/2019

Are You Looking? Grounding to Multiple Modalities in Vision-and-Language Navigation

Vision-and-Language Navigation (VLN) requires grounding instructions, su...

0 Ronghang Hu, et al. ∙

research

∙ 04/22/2019

Tetra-Tagging: Word-Synchronous Parsing with Linear-Time Inference

We present a constituency parsing algorithm that maps from word-aligned ...

0 Nikita Kitaev, et al. ∙

research

∙ 04/02/2019

Pragmatically Informative Text Generation

We improve the informativeness of models for conditional text generation...

0 Sheng Shen, et al. ∙

Dan Klein

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