Rishabh Agarwal

Artificial Intelligence · with Bansal · 2024

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 30 citations into it

Whom Rishabh Agarwal trusts

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma (in Artificial Intelligence)
2. Jimmy Ba (in Artificial Intelligence)

Papers from Rishabh Agarwal's perspective

Ordered by how strongly the researchers Rishabh Agarwal trusts endorse each paper. Same corpus, a different order for every researcher.

1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
2. Training Verifiers to Solve Math Word Problems
3. Decoupled Weight Decay Regularization
4. Learning to summarize from human feedback
5. WebGPT: Browser-assisted question-answering with human feedback
6. Evaluating Large Language Models Trained on Code (arXiv.org)
7. Scaling Instruction-Finetuned Language Models (Journal of machine learning research)
8. Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them
9. Solving math word problems with process- and outcome-based feedback
10. Improving language models by retrieving from trillions of tokens

Their papers

• Generative Verifiers: Reward Modeling as Next-Token Prediction (2024) — 490 citations