Search Results for author: Griffin Adams

Found 10 papers, 5 papers with code

SPEER: Sentence-Level Planning of Long Clinical Summaries via Embedded Entity Retrieval

no code implementations4 Jan 2024 Griffin Adams, Jason Zucker, Noémie Elhadad

To increase entity coverage, we train a smaller, encoder-only model to predict salient entities, which are treated as content-plans to guide the LLM.

Entity Retrieval Retrieval +1

From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting

no code implementations8 Sep 2023 Griffin Adams, Alexander Fabbri, Faisal Ladhak, Eric Lehman, Noémie Elhadad

We conduct a human preference study on 100 CNN DailyMail articles and find that that humans prefer GPT-4 summaries that are more dense than those generated by a vanilla prompt and almost as dense as human written summaries.

Informativeness

Generating EDU Extracts for Plan-Guided Summary Re-Ranking

1 code implementation28 May 2023 Griffin Adams, Alexander R. Fabbri, Faisal Ladhak, Kathleen McKeown, Noémie Elhadad

Similarly, on 1k samples from CNN / DM, we show that prompting GPT-3 to follow EDU plans outperforms sampling-based methods by 1. 05 ROUGE-2 F1 points.

Language Modelling Re-Ranking

What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization

1 code implementation12 May 2023 Griffin Adams, Bichlien H Nguyen, Jake Smith, Yingce Xia, Shufang Xie, Anna Ostropolets, Budhaditya Deb, Yuan-Jyue Chen, Tristan Naumann, Noémie Elhadad

Summarization models often generate text that is poorly calibrated to quality metrics because they are trained to maximize the likelihood of a single reference (MLE).

A Meta-Evaluation of Faithfulness Metrics for Long-Form Hospital-Course Summarization

no code implementations7 Mar 2023 Griffin Adams, Jason Zucker, Noémie Elhadad

To better understand the limitations of abstractive systems, as well as the suitability of existing evaluation metrics, we benchmark faithfulness metrics against fine-grained human annotations for model-generated summaries of a patient's Brief Hospital Course.

Domain Adaptation Sentence

Learning to Revise References for Faithful Summarization

1 code implementation13 Apr 2022 Griffin Adams, Han-Chin Shing, Qing Sun, Christopher Winestock, Kathleen McKeown, Noémie Elhadad

In real-world scenarios with naturally occurring datasets, reference summaries are noisy and may contain information that cannot be inferred from the source text.

Attribute Clinical Knowledge +2

Resolving Implicit Coordination in Multi-Agent Deep Reinforcement Learning with Deep Q-Networks & Game Theory

1 code implementation8 Dec 2020 Griffin Adams, Sarguna Janani Padmanabhan, Shivang Shekhar

We address two major challenges of implicit coordination in multi-agent deep reinforcement learning: non-stationarity and exponential growth of state-action space, by combining Deep-Q Networks for policy learning with Nash equilibrium for action selection.

OpenAI Gym Reinforcement Learning (RL)

Zero-Shot Clinical Acronym Expansion via Latent Meaning Cells

1 code implementation29 Sep 2020 Griffin Adams, Mert Ketenci, Shreyas Bhave, Adler Perotte, Noémie Elhadad

We introduce Latent Meaning Cells, a deep latent variable model which learns contextualized representations of words by combining local lexical context and metadata.

Representation Learning

TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes

no code implementations30 Nov 2018 Monica Agrawal, Griffin Adams, Nathan Nussbaum, Benjamin Birnbaum

In this work, we present TIFTI (Temporally Integrated Framework for Treatment Intervals), a robust framework for extracting oral drug treatment intervals from a patient's unstructured notes.

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