Search Results for author:
Found 8 papers, 4 papers with code
RULER: What's the Real Context Size of Your Long-Context Language Models?
Despite achieving nearly perfect accuracy in the vanilla NIAH test, all models exhibit large performance drops as the context length increases.
Transducers with Pronunciation-aware Embeddings for Automatic Speech Recognition
This paper proposes Transducers with Pronunciation-aware Embeddings (PET).
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
Building on the recent progress in open-source LLMs, our proposed prompting novelty, and some brute-force scaling, we construct OpenMathInstruct-1, a math instruction tuning dataset with 1. 8M problem-solution pairs.
Ranked #1 on
Math Word Problem Solving
on MAWPS
(using extra training data)
Efficient Sequence Transduction by Jointly Predicting Tokens and Durations
TDT models for Speech Recognition achieve better accuracy and up to 2. 82X faster inference than conventional Transducers.
Intent Classification
Intent Classification and Slot Filling
+3
Accidental Learners: Spoken Language Identification in Multilingual Self-Supervised Models
In this paper, we extend previous self-supervised approaches for language identification by experimenting with Conformer based architecture in a multilingual pre-training paradigm.
Multi-blank Transducers for Speech Recognition
This paper proposes a modification to RNN-Transducer (RNN-T) models for automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
A Compact End-to-End Model with Local and Global Context for Spoken Language Identification
We introduce TitaNet-LID, a compact end-to-end neural network for Spoken Language Identification (LID) that is based on the ContextNet architecture.
Lessons from the AdKDD'21 Privacy-Preserving ML Challenge
Designing data sharing mechanisms providing performance and strong privacy guarantees is a hot topic for the Online Advertising industry.
