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Workshop
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Transformer-based Causal Language Models from a Meta-Learning Perspective
Xinbo Wu · Lav Varshney
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Workshop
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Transformer-Based Large Language Models Are Not General Learners: A Universal Circuit Perspective
Yang Chen · Yitao Liang · Zhouchen Lin
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Poster
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Wed 8:45
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Blockwise Parallel Transformers for Large Context Models
Hao Liu · Pieter Abbeel
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Workshop
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Trained Transformers Learn Linear Models In-Context
Ruiqi Zhang · Spencer Frei · Peter Bartlett
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Workshop
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Trained Transformers Learn Linear Models In-Context
Ruiqi Zhang · Spencer Frei · Peter Bartlett
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Workshop
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Can Transformers In-Context Learn Task Mixtures?
Nilesh Tripuraneni · Lyric Doshi · Steve Yadlowsky
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Workshop
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Can Transformer Models Generalize Via In-Context Learning Beyond Pretraining Data?
Steve Yadlowsky · Lyric Doshi · Nilesh Tripuraneni
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Workshop
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DDxT: Deep Generative Transformer Models for Differential Diagnosis
Mohammad Mahmudul Alam · Edward Raff · Tim Oates · Cynthia Matuszek
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Poster
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Wed 8:45
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MEGABYTE: Predicting Million-byte Sequences with Multiscale Transformers
LILI YU · Daniel Simig · Colin Flaherty · Armen Aghajanyan · Luke Zettlemoyer · Mike Lewis
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Workshop
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Optimizing protein language models with Sentence Transformers
Istvan Redl
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Poster
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Thu 8:45
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TabMT: Generating tabular data with masked transformers
Manbir Gulati · Paul Roysdon
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Workshop
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Ring Attention with Blockwise Transformers for Near-Infinite Context
Hao Liu · Matei A Zaharia · Pieter Abbeel
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