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UNC Chapel Hill
- Chapel Hill
- archiki.github.io
- @ArchikiPrasad
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Code for paper: "LASeR: Learning to Adaptively Select Reward Models with Multi-Arm Bandits"
Code for paper "AdaCAD: Adaptively Decoding to Balance Conflicts between Contextual and Parametric Knowledge"
PyTorch code for System-1.x: Learning to Balance Fast and Slow Planning with Language Models
Code for ACL 2024 paper "Soft Self-Consistency Improves Language Model Agents"
Code for paper "Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs"
A curated list of research papers and resources on code-switching
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.
XTREME is a benchmark for the evaluation of the cross-lingual generalization ability of pre-trained multilingual models that covers 40 typologically diverse languages and includes nine tasks.
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
Speech Recognition using DeepSpeech2.
Real Time Speech Enhancement in the Waveform Domain (Interspeech 2020)We provide a PyTorch implementation of the paper Real Time Speech Enhancement in the Waveform Domain. In which, we present a ca…