Alex Tamkin
14 papers · 2019–2025 · 6 venues · across top CS/AI venues
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Machine Learning
(11)
Artificial Intelligence
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Learning Types Β· Machine Learning
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Deep Learning
(7)
Core AI
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Natural Language Processing
(4)
Application Areas
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Computer Vision
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Mathematics & Optimization
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Keywords
transfer learning
(3)
self-supervised learning
(2)
representation learning
(2)
active learning
(2)
data augmentation
(2)
pre-trained language model
(2)
task ambiguity
(2)
policy optimization
(1)
in-context learning
(1)
few-shot learning
(1)
natural language inference
(1)
vector quantization
(1)
cross-lingual transfer
(1)
neural network interpretability
(1)
adversarial learning
(1)
markov decision process
(1)
reinforcement learning from human feedback
(1)
continued pretraining
(1)
distributional reinforcement learning
(1)
domain adaptation
(1)
Papers
Eliciting Human Preferences with Language Models
ICLR 2025
Codebook Features: Sparse and Discrete Interpretability for Neural Networks
ICML 2024
Many-shot Jailbreaking
NeurIPS 2024
Feature Dropout: Revisiting the Role of Augmentations in Contrastive Learning
NeurIPS 2023
Oolong: Investigating What Makes Transfer Learning Hard with Controlled Studies
EMNLP 2023
Task Ambiguity in Humans and Language Models
ICLR 2023
Turbulence in Focus: Benchmarking Scaling Behavior of 3D Volumetric Super-Resolution with BLASTNet 2.0 Data
NeurIPS 2023
Active Learning Helps Pretrained Models Learn the Intended Task
NeurIPS 2022
DABS 2.0: Improved Datasets and Algorithms for Universal Self-Supervision
NeurIPS 2022
Viewmaker Networks: Learning Views for Unsupervised Representation Learning
ICLR 2021
Being Optimistic to Be Conservative: Quickly Learning a CVaR Policy
AAAI 2020
Investigating Transferability in Pretrained Language Models
EMNLP 2020
Language Through a Prism: A Spectral Approach for Multiscale Language Representations
NeurIPS 2020
Recursive Routing Networks: Learning to Compose Modules for Language Understanding
NAACL 2019