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8fad1ce6d16f654936b98662fce84c5d-Paper-Conference.pdf

D: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages

Neural Information Processing Systems

D comprises 52.6k question-answer pairs from 16 countries/regions,

8e7768122f3eeec6d77cd2b424b72413-Paper-Datasets_and_Benchmarks_Track.pdf

Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context

Neural Information Processing Systems

Transformers can efficiently learn in-context from example demonstrations.

8d57f138d14fdfdc520eb29804116d9e-Paper-Conference.pdf

8d35d225230a9d77b29c1dd300e48ad9-Paper-Conference.pdf

End-To-End Causal Effect Estimation from Unstructured Natural Language Data

Neural Information Processing Systems

Work done during internship at Meta AI. 38th Conference on Neural Information Processing Systems (NeurIPS 2024).

Personalized Federated Learning via Feature Distribution Adaptation

Neural Information Processing Systems

Federated learning (FL) is a distributed learning framework that leverages commonalities between distributed client datasets to train a global model.

Many-Shot In-Context Learning Rishabh Agarwal, A vi Singh

Neural Information Processing Systems

LLMs excel at few-shot in-context learning (ICL) - learning from a few input-output examples ("shots") provided in context at inference, without any weight updates.

Few-shot Algorithms for Consistent Neural Decoding (FALCON) Benchmark Brianna M. Karpowicz 1,2 Joel Y e

Neural Information Processing Systems

However, progress is limited by a lack of standardized datasets and comparison metrics, causing methods to be compared in an ad hoc manner.