11 citations · 28 across the 13 of their papers we have counts for
13 papers
The Llama 4 Herd: Architecture, Training, Evaluation, and Deployment Notes
Redacted by arXiv
This document consolidates publicly reported technical details about Metas Llama 4 model family. It summarizes (i) released variants (Scout and Maverick) and the broader herd conte…
Generating Faithful and Complete Hospital-Course Summaries from the Electronic Health Record
Griffin Adams
The rapid adoption of Electronic Health Records (EHRs) has been instrumental in streamlining administrative tasks, increasing transparency, and enabling continuity of care across p…
SPEER: Sentence-Level Planning of Long Clinical Summaries via Embedded Entity Retrieval
Griffin Adams, Jason Zucker, Noémie Elhadad
Clinician must write a lengthy summary each time a patient is discharged from the hospital. This task is time-consuming due to the sheer number of unique clinical concepts covered…
From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
Griffin Adams, Alexander Fabbri, Faisal Ladhak +2
Selecting the ``right'' amount of information to include in a summary is a difficult task. A good summary should be detailed and entity-centric without being overly dense and hard…
Generating EDU Extracts for Plan-Guided Summary Re-Ranking
Griffin Adams, Alexander R. Fabbri, Faisal Ladhak +2
Two-step approaches, in which summary candidates are generated-then-reranked to return a single summary, can improve ROUGE scores over the standard single-step approach. Yet, stand…
What are the Desired Characteristics of Calibration Sets? Identifying Correlates on Long Form Scientific Summarization
Griffin Adams, Bichlien H Nguyen, Jake Smith +7
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). To address th…
A Meta-Evaluation of Faithfulness Metrics for Long-Form Hospital-Course Summarization
Griffin Adams, Jason Zucker, Noémie Elhadad
Long-form clinical summarization of hospital admissions has real-world significance because of its potential to help both clinicians and patients. The faithfulness of summaries is…
Learning to Revise References for Faithful Summarization
Griffin Adams, Han-Chin Shing, Qing Sun +3
In real-world scenarios with naturally occurring datasets, reference summaries are noisy and may contain information that cannot be inferred from the source text. On large news cor…
Investigating Crowdsourcing Protocols for Evaluating the Factual Consistency of Summaries
Xiangru Tang, Alexander Fabbri, Haoran Li +6
Current pre-trained models applied to summarization are prone to factual inconsistencies which either misrepresent the source text or introduce extraneous information. Thus, compar…
What's in a Summary? Laying the Groundwork for Advances in Hospital-Course Summarization
Griffin Adams, Emily Alsentzer, Mert Ketenci +2
Summarization of clinical narratives is a long-standing research problem. Here, we introduce the task of hospital-course summarization. Given the documentation authored throughout…
Resolving Implicit Coordination in Multi-Agent Deep Reinforcement Learning with Deep Q-Networks & Game Theory
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 Dee…
Zero-Shot Clinical Acronym Expansion via Latent Meaning Cells
Griffin Adams, Mert Ketenci, Shreyas Bhave +2
We introduce Latent Meaning Cells, a deep latent variable model which learns contextualized representations of words by combining local lexical context and metadata. Metadata can r…
TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes
Monica Agrawal, Griffin Adams, Nathan Nussbaum +1
Oral drugs are becoming increasingly common in oncology care. In contrast to intravenous chemotherapy, which is administered in the clinic and carefully tracked via structure elect…