2.2k citations · 5.1k across the 21 of their papers we have counts for
24 papers
OTel: Open Telco AI Datasets, Benchmarks, and Models
Farbod Tavakkoli, Gregory Diamos, Kenneth Church +19
We present Open Telco (OTel), an open telecom AI resource that releases derived telecom datasets for retrieval, reranking, instruction tuning, and safety/abstention, together with…
OTel: Building Domain-Specialized Telecom LLM Foundations for Intelligent Networks
Farbod Tavakkoli, Roderic Paulk, Jorden Terrazas +9
Frontier AI models have advanced rapidly, but they still struggle with telecom-specific tasks. We present Open Telco (OTel), an open telecom AI resource with derived datasets for r…
SIFT-50M: A Large-Scale Multilingual Dataset for Speech Instruction Fine-Tuning
Prabhat Pandey, Rupak Vignesh Swaminathan, K V Vijay Girish +4
We introduce SIFT (Speech Instruction Fine-Tuning), a 50M-example dataset designed for instruction fine-tuning and pre-training of speech-text large language models (LLMs). SIFT-50…
Banishing LLM Hallucinations Requires Rethinking Generalization
Johnny Li, Saksham Consul, Eda Zhou +9
Despite their powerful chat, coding, and reasoning abilities, Large Language Models (LLMs) frequently hallucinate. Conventional wisdom suggests that hallucinations are a consequenc…
DataPerf: Benchmarks for Data-Centric AI Development
Mark Mazumder, Colby Banbury, Xiaozhe Yao +42
Machine learning research has long focused on models rather than datasets, and prominent datasets are used for common ML tasks without regard to the breadth, difficulty, and faithf…
The People's Speech: A Large-Scale Diverse English Speech Recognition Dataset for Commercial Usage
Daniel Galvez, Greg Diamos, Juan Ciro +7
The People's Speech is a free-to-download 30,000-hour and growing supervised conversational English speech recognition dataset licensed for academic and commercial usage under CC-B…