← Authors

Richard Zemel

65 papers · 2010–2025 · 13 conferences · across top CS/AI conferences

Achievements

🧭 Keyword Pioneer 🌍 Conference Polyglot (13) πŸ—ΊοΈ Taxonomy Completionist (18) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (9) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (15) 🌟 Keyword Trendsetter Combo (7) πŸ“› The Namer 🀝 Dynamic Duo (10) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ”¬ Deep Specialist (11) 🧬 Topic Evolution πŸ† Keyword Champion (2) πŸ—ƒοΈ Keyword Collector (248) ⚑ Prolific Year (7) πŸ’Ž Century Club (65) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (14) πŸš€ Conference Pioneer

Conferences

ICML (17) NIPS (17) ICLR (10) EMNLP (5) NAACL (4) ACL (3) AISTATS (3) CLEAR (1) CORL (1) CVPR (1) ECCV (1) ICCV (1) UAI (1)

Top co-authors

Raquel Urtasun (10) Renjie Liao (9) Rahul Gupta (8) David Madras (7) Elliot Creager (7) Jake Snell (6) Ninareh Mehrabi (6) Aram Galstyan (6) Kai-Wei Chang (6) Toniann Pitassi (6)

Keywords

few-shot learning (6) representation learning (6) large language model (5) zero-shot learning (5) generative model (4) graph neural network (4) neural network (4) latent variable model (3) unsupervised learning (3) variational autoencoder (3) graphical model (2) structured output learning (2) dynamical system (2) metric learning (2) text classification (2) text generation (2) causal inference (2) imitation learning (2) variational inference (2) algorithmic fairness (2)

Papers

Towards Safety Reasoning in LLMs: AI-agentic Deliberation for Policy-embedded CoT Data Creation ACL 2025
Adaptive Elicitation of Latent Information Using Natural Language ICML 2025
QuEst: Enhancing Estimates of Quantile-Based Distributional Measures Using Model Predictions ICML 2025
Controlling the World by Sleight of Hand ECCV 2024
Out of the Ordinary: Spectrally Adapting Regression for Covariate Shift ICML 2024
Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models ICLR 2024
Tokenization Matters: Navigating Data-Scarce Tokenization for Gender Inclusive Language Technologies NAACL 2024
The steerability of large language models toward data-driven personas NAACL 2024
Attribute Controlled Fine-tuning for Large Language Models: A Case Study on Detoxification EMNLP 2024
Whiteboard-of-Thought: Thinking Step-by-Step Across Modalities EMNLP 2024
Training-free Deep Concept Injection Enables Language Models for Video Question Answering EMNLP 2024
FLIRT: Feedback Loop In-context Red Teaming EMNLP 2024
Toward Informal Language Processing: Knowledge of Slang in Large Language Models NAACL 2024
Resolving Ambiguities in Text-to-Image Generative Models ACL 2023
Quantile Risk Control: A Flexible Framework for Bounding the Probability of High-Loss Predictions ICLR 2023
SurfsUP: Learning Fluid Simulation for Novel Surfaces ICCV 2023
Coordinated Replay Sample Selection for Continual Federated Learning EMNLP 2023
Amortized Causal Discovery: Learning to Infer Causal Graphs from Time-Series Data CLEAR 2022
Mapping the Multilingual Margins: Intersectional Biases of Sentiment Analysis Systems in English, Spanish, and Arabic ACL 2022
Semantically Informed Slang Interpretation NAACL 2022
NP-DRAW: A Non-Parametric Structured Latent Variable Model for Image Generation UAI 2021
Theoretical bounds on estimation error for meta-learning ICLR 2021
A PAC-Bayesian Approach to Generalization Bounds for Graph Neural Networks ICLR 2021
Bayesian Few-Shot Classification with One-vs-Each PΓ³lya-Gamma Augmented Gaussian Processes ICLR 2021
Wandering within a world: Online contextualized few-shot learning ICLR 2021
Environment Inference for Invariant Learning ICML 2021
On Monotonic Linear Interpolation of Neural Network Parameters ICML 2021
Learning a Universal Template for Few-shot Dataset Generalization ICML 2021
SketchEmbedNet: Learning Novel Concepts by Imitating Drawings ICML 2021
Optimizing Long-term Social Welfare in Recommender Systems: A Constrained Matching Approach ICML 2020
Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling ICML 2020
Causal Modeling for Fairness In Dynamical Systems ICML 2020
Understanding the Limitations of Conditional Generative Models ICLR 2020
SMILe: Scalable Meta Inverse Reinforcement Learning through Context-Conditional Policies NIPS 2019
LanczosNet: Multi-Scale Deep Graph Convolutional Networks ICLR 2019
Excessive Invariance Causes Adversarial Vulnerability ICLR 2019
Aggregated Momentum: Stability Through Passive Damping ICLR 2019
Understanding the Origins of Bias in Word Embeddings ICML 2019
Flexibly Fair Representation Learning by Disentanglement ICML 2019
Lorentzian Distance Learning for Hyperbolic Representations ICML 2019
A Divergence Minimization Perspective on Imitation Learning Methods CORL 2019
Incremental Few-Shot Learning with Attention Attractor Networks NIPS 2019
Efficient Graph Generation with Graph Recurrent Attention Networks NIPS 2019
Reviving and Improving Recurrent Back-Propagation ICML 2018
Predict Responsibly: Improving Fairness and Accuracy by Learning to Defer NIPS 2018
Learning Adversarially Fair and Transferable Representations ICML 2018
Adversarial Distillation of Bayesian Neural Network Posteriors ICML 2018
Neural Relational Inference for Interacting Systems ICML 2018
Learning Latent Subspaces in Variational Autoencoders NIPS 2018
Neural Guided Constraint Logic Programming for Program Synthesis NIPS 2018
Dualing GANs NIPS 2017
Prototypical Networks for Few-shot Learning NIPS 2017
Few-Shot Learning Through an Information Retrieval Lens NIPS 2017
Causal Effect Inference with Deep Latent-Variable Models NIPS 2017
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks NIPS 2016
Learning Deep Parsimonious Representations NIPS 2016
Exploring Models and Data for Image Question Answering NIPS 2015
Skip-Thought Vectors NIPS 2015
A Multiplicative Model for Learning Distributed Text-Based Attribute Representations NIPS 2014
On the Representational Efficiency of Restricted Boltzmann Machines NIPS 2013
Exploring Compositional High Order Pattern Potentials for Structured Output Learning CVPR 2013
A Determinantal Point Process Latent Variable Model for Inhibition in Neural Spiking Data NIPS 2013
Randomized Optimum Models for Structured Prediction AISTATS 2012
Structured Output Learning with High Order Loss Functions AISTATS 2012
HOP-MAP: Efficient Message Passing with High Order Potentials AISTATS 2010