Victor Veitch
24 papers · 2019–2025 · 7 conferences · across top CS/AI conferences
Achievements
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π Academic Marathon (6) π§ Keyword Pioneer π Interdisciplinary Bridge π Conference Polyglot (7) π Cross-Pollinator (13)
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(29)
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(5)
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Mega-Team
(40)
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Deep Specialist
(10)
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(2)
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(7)
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Century Club
(24)
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Keyword Collector
(72)
Conferences
NIPS (10)
ICML (5)
ICLR (4)
UAI (2)
AISTATS (1)
JMLR (1)
NAACL (1)
Top co-authors
Keywords
causal inference
(10)
representation learning
(4)
observational datum
(3)
domain generalization
(3)
text classification
(2)
embedding learning
(2)
network embedding
(2)
unobserved confounding
(2)
policy optimization
(1)
reward modeling
(1)
sentiment analysis
(1)
domain adaptation
(1)
knowledge distillation
(1)
language model alignment
(1)
stochastic gradient descent
(1)
graph embedding
(1)
model alignment
(1)
empirical risk minimization
(1)
sensitivity analysis
(1)
reinforcement learning from human feedback
(1)
Papers
RATE: Causal Explainability of Reward Models with Imperfect Counterfactuals
ICML 2025
The Geometry of Categorical and Hierarchical Concepts in Large Language Models
ICLR 2025
On the Origins of Linear Representations in Large Language Models
ICML 2024
BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling
NIPS 2024
The Linear Representation Hypothesis and the Geometry of Large Language Models
ICML 2024
Transforming and Combining Rewards for Aligning Large Language Models
ICML 2024
Efficient Conditionally Invariant Representation Learning
ICLR 2023
Uncovering Meanings of Embeddings via Partial Orthogonality
NIPS 2023
Causal Context Connects Counterfactual Fairness to Robust Prediction and Group Fairness
NIPS 2023
Concept Algebra for (Score-Based) Text-Controlled Generative Models
NIPS 2023
Causal Estimation for Text Data with (Apparent) Overlap Violations
ICLR 2023
Using Embeddings for Causal Estimation of Peer Influence in Social Networks
NIPS 2022
Underspecification Presents Challenges for Credibility in Modern Machine Learning
JMLR 2022
Invariant and Transportable Representations for Anti-Causal Domain Shifts
NIPS 2022
Invariant representation learning for treatment effect estimation
UAI 2021
Counterfactual Invariance to Spurious Correlations in Text Classification
NIPS 2021
Valid Causal Inference with (Some) Invalid Instruments
ICML 2021
Causal Effects of Linguistic Properties
NAACL 2021
Sense and Sensitivity Analysis: Simple Post-Hoc Analysis of Bias Due to Unobserved Confounding
NIPS 2020
Adapting Text Embeddings for Causal Inference
UAI 2020
Empirical Risk Minimization and Stochastic Gradient Descent for Relational Data
AISTATS 2019
Using Embeddings to Correct for Unobserved Confounding in Networks
NIPS 2019
Adapting Neural Networks for the Estimation of Treatment Effects
NIPS 2019
Non-vacuous Generalization Bounds at the ImageNet Scale: a PAC-Bayesian Compression Approach
ICLR 2019