← Authors

Rishabh Agarwal

37 papers · 2019–2025 · 7 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (7) πŸƒ Academic Marathon (6) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (4) 🌈 Renaissance Researcher (5) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ‘₯ Mega-Team (22) πŸ—ƒοΈ Keyword Collector (99) πŸ’Ž Century Club (37) ⚑ Prolific Year (6) πŸ”₯ Unstoppable (7)

Conferences

ICLR (15) ICML (10) NIPS (7) AISTATS (2) AAAI (1) COLING (1) SEMEVAL (1)

Top co-authors

Aviral Kumar (8) Pablo Samuel Castro (7) Aleksandra Faust (5) Marc G Bellemare (5) George Tucker (4) Jesse Farebrother (4) Sergey Levine (4) Aaron Courville (4) Charline Le Lan (4) Mohammad Norouzi (3)

Keywords

reinforcement learning (4) deep reinforcement learning (4) offline reinforcement learning (3) neural network (3) policy learning (2) large language model (2) transformer-based model (2) state representation (2) emphasis selection (2) policy evaluation (2) value iteration (2) model selection (1) few-shot learning (1) imitation learning (1) stochastic gradient descent (1) temporal difference learning (1) representation learning (1) in-context learning (1) kl divergence (1) text classification (1)

Papers

Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models ICLR 2025
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models ICLR 2025
Reward-Guided Prompt Evolving in Reinforcement Learning for LLMs ICML 2025
Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling ICLR 2025
Training Language Models to Self-Correct via Reinforcement Learning ICLR 2025
Generative Verifiers: Reward Modeling as Next-Token Prediction ICLR 2025
Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling ICLR 2025
Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning ICLR 2025
On scalable oversight with weak LLMs judging strong LLMs NIPS 2024
Many-Shot In-Context Learning NIPS 2024
DistillSpec: Improving Speculative Decoding via Knowledge Distillation ICLR 2024
On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes ICLR 2024
SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning ICML 2024
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL ICML 2024
Bigger, Better, Faster: Human-level Atari with human-level efficiency ICML 2023
Revisiting Bellman Errors for Offline Model Selection ICML 2023
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research NIPS 2023
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces AISTATS 2023
Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks ICLR 2023
Investigating Multi-task Pretraining and Generalization in Reinforcement Learning ICLR 2023
Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes ICLR 2023
Bootstrapped Representations in Reinforcement Learning ICML 2023
The Dormant Neuron Phenomenon in Deep Reinforcement Learning ICML 2023
On the Generalization of Representations in Reinforcement Learning AISTATS 2022
Reincarnating Reinforcement Learning: Reusing Prior Computation to Accelerate Progress NIPS 2022
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization ICLR 2022
Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation AAAI 2022
Contrastive Behavioral Similarity Embeddings for Generalization in Reinforcement Learning ICLR 2021
Neural Additive Models: Interpretable Machine Learning with Neural Nets NIPS 2021
Deep Reinforcement Learning at the Edge of the Statistical Precipice NIPS 2021
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning ICLR 2021
IITK at SemEval-2020 Task 10: Transformers for Emphasis Selection SEMEVAL 2020
IITK at SemEval-2020 Task 10: Transformers for Emphasis Selection COLING 2020
An Optimistic Perspective on Offline Reinforcement Learning ICML 2020
Revisiting Fundamentals of Experience Replay ICML 2020
RL Unplugged: A Suite of Benchmarks for Offline Reinforcement Learning NIPS 2020
Learning to Generalize from Sparse and Underspecified Rewards ICML 2019