Frederic Sala
32 papers · 2018–2025 · 9 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (63) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Grand Slam
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Keyword Champion
(11)
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Dynamic Duo
(13)
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Triple Crown
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Deep Specialist
(13)
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Conference Pioneer
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Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Renaissance Researcher
(6)
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Keyword Collector
(164)
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Research topics
Machine Learning
(31)
Learning Types Β· Machine Learning
(24)
Artificial Intelligence
(14)
Application Areas
(11)
Core Methods
(11)
Optimization & Theory
(11)
Deep Learning
(9)
Core AI
(9)
Learning Paradigms
(6)
Learning Types Β· Deep Learning
(6)
Natural Language Processing
(4)
Knowledge & Reasoning
(3)
Models
(3)
Mathematics & Optimization
(2)
Generation
(2)
Keywords
weak supervision
(11)
semi-supervised learning
(3)
zero-shot learning
(3)
representation learning
(3)
foundation model
(3)
large language model
(3)
language model
(3)
hyperbolic embedding
(3)
label estimation
(2)
threshold-based method
(2)
domain adaptation
(2)
probabilistic label
(2)
metric space
(2)
latent variable model
(2)
few-shot learning
(2)
instruction tuning
(2)
label noise
(2)
transfer learning
(2)
threshold-based labeling
(2)
metric learning
(1)
Papers
Personalize Your LLM: Fake it then Align it
NAACL 2025
Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL
ICML 2025
Weak-to-Strong Generalization Through the Data-Centric Lens
ICLR 2025
Look Whoβs Talking Now: Covert Channels From Biased LLMs
EMNLP 2024
OTTER: Effortless Label Distribution Adaptation of Zero-shot Models
NeurIPS 2024
Pearls from Pebbles: Improved Confidence Functions for Auto-labeling
NeurIPS 2024
Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks
NeurIPS 2024
The ALCHEmist: Automated Labeling 500x CHEaper than LLM Data Annotators
NeurIPS 2024
Zero-Shot Robustification of Zero-Shot Models
ICLR 2024
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
NeurIPS 2023
Generative Modeling Helps Weak Supervision (and Vice Versa)
ICLR 2023
Geometry-Aware Adaptation for Pretrained Models
NeurIPS 2023
Mitigating Source Bias for Fairer Weak Supervision
NeurIPS 2023
Promises and Pitfalls of Threshold-based Auto-labeling
NeurIPS 2023
Skill-it! A data-driven skills framework for understanding and training language models
NeurIPS 2023
The Cost of Compression: Investigating the Impact of Compression on Parametric Knowledge in Language Models
EMNLP 2023
Train 'n Trade: Foundations of Parameter Markets
NeurIPS 2023
AutoWS-Bench-101: Benchmarking Automated Weak Supervision with 100 Labels
NeurIPS 2022
Lifting Weak Supervision To Structured Prediction
NeurIPS 2022
NAS-Bench-360: Benchmarking Neural Architecture Search on Diverse Tasks
NeurIPS 2022
Shoring up the foundations: fusing model embeddings and weak supervision
UAI 2022
Universalizing Weak Supervision
ICLR 2022
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation
AISTATS 2021
Cut out the annotator, keep the cutout: better segmentation with weak supervision
ICLR 2021
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
ICML 2020
Ivy: Instrumental Variable Synthesis for Causal Inference
AISTATS 2020
Low-Dimensional Hyperbolic Knowledge Graph Embeddings
ACL 2020
Learning Dependency Structures for Weak Supervision Models
ICML 2019
Learning Mixed-Curvature Representations in Product Spaces
ICLR 2019
Multi-Resolution Weak Supervision for Sequential Data
NeurIPS 2019
Training Complex Models with Multi-Task Weak Supervision
AAAI 2019
Representation Tradeoffs for Hyperbolic Embeddings
ICML 2018