1 code implementation • 29 Apr 2024 • Justin Zhao, Timothy Wang, Wael Abid, Geoffrey Angus, Arnav Garg, Jeffery Kinnison, Alex Sherstinsky, Piero Molino, Travis Addair, Devvret Rishi
LoRAX powers LoRA Land, a web application that hosts 25 LoRA fine-tuned Mistral-7B LLMs on a single NVIDIA A100 GPU with 80GB memory.
no code implementations • 3 Feb 2023 • Piero Molino, Jacopo Tagliabue
We examine how much of the contemporary progress in artificial intelligence (and, specifically, in natural language processing), can be, more or less directly, traced back to the seminal work and ideas of the Austrian-British philosopher Ludwig Wittgenstein, with particular focus on his late views.
2 code implementations • 8 Nov 2021 • Avanika Narayan, Piero Molino, Karan Goel, Willie Neiswanger, Christopher Ré
LBT provides a configurable interface for controlling training and customizing evaluation, a standardized training framework for eliminating confounding variables, and support for multi-objective evaluation.
2 code implementations • 16 Jul 2021 • Piero Molino, Christopher Ré
In this article we will describe how ML systems are currently structured, highlight important factors for their success and adoption, what are the issues current ML systems are facing and how the systems we developed addressed them.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Lei Shu, Alexandros Papangelis, Yi-Chia Wang, Gokhan Tur, Hu Xu, Zhaleh Feizollahi, Bing Liu, Piero Molino
This work introduces Focused-Variation Network (FVN), a novel model to control language generation.
no code implementations • 28 Jan 2020 • Yue Weng, Sai Sumanth Miryala, Chandra Khatri, Runze Wang, Huaixiu Zheng, Piero Molino, Mahdi Namazifar, Alexandros Papangelis, Hugh Williams, Franziska Bell, Gokhan Tur
As a baseline approach, we trained task-specific Statistical Language Models (SLM) and fine-tuned state-of-the-art Generalized Pre-training (GPT) Language Model to re-rank the n-best ASR hypotheses, followed by a model to identify the dialog act and slots.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +3
no code implementations • 24 Jan 2020 • Andrea Madotto, Mahdi Namazifar, Joost Huizinga, Piero Molino, Adrien Ecoffet, Huaixiu Zheng, Alexandros Papangelis, Dian Yu, Chandra Khatri, Gokhan Tur
In this work, we propose to use the exploration approach of Go-Explore for solving text-based games.
4 code implementations • 17 Jan 2020 • Alexandros Papangelis, Mahdi Namazifar, Chandra Khatri, Yi-Chia Wang, Piero Molino, Gokhan Tur
Plato has been designed to be easy to understand and debug and is agnostic to the underlying learning frameworks that train each component.
1 code implementation • 20 Dec 2019 • Avishek Joey Bose, Ankit Jain, Piero Molino, William L. Hamilton
We consider the task of few shot link prediction on graphs.
7 code implementations • ICLR 2020 • Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, Rosanne Liu
Large transformer-based language models (LMs) trained on huge text corpora have shown unparalleled generation capabilities.
3 code implementations • 17 Sep 2019 • Piero Molino, Yaroslav Dudin, Sai Sumanth Miryala
In this work we present Ludwig, a flexible, extensible and easy to use toolbox which allows users to train deep learning models and use them for obtaining predictions without writing code.
1 code implementation • IJCNLP 2019 • Lei Shu, Hu Xu, Bing Liu, Piero Molino
Dialogue management (DM) plays a key role in the quality of the interaction with the user in a task-oriented dialogue system.
1 code implementation • WS 2019 • Lei Shu, Piero Molino, Mahdi Namazifar, Hu Xu, Bing Liu, Huaixiu Zheng, Gokhan Tur
It is based on a simple and practical yet very effective sequence-to-sequence approach, where language understanding and state tracking tasks are modeled jointly with a structured copy-augmented sequential decoder and a multi-label decoder for each slot.
4 code implementations • WS 2019 • Alexandros Papangelis, Yi-Chia Wang, Piero Molino, Gokhan Tur
and their own objectives, and can only interact via natural language they generate.
2 code implementations • ACL 2019 • Piero Molino, Yang Wang, Jiawei Zhang
Embeddings are a fundamental component of many modern machine learning and natural language processing models.
no code implementations • ICLR 2019 • Piero Molino, Yang Wang, Jiawei Zhang
Embeddings are a fundamental component of many modern machine learning and natural language processing models.
no code implementations • 1 Aug 2018 • Jiawei Zhang, Yang Wang, Piero Molino, Lezhi Li, David S. Ebert
We present Manifold, a framework that utilizes visual analysis techniques to support interpretation, debugging, and comparison of machine learning models in a more transparent and interactive manner.
22 code implementations • NeurIPS 2018 • Rosanne Liu, Joel Lehman, Piero Molino, Felipe Petroski Such, Eric Frank, Alex Sergeev, Jason Yosinski
In this paper we show a striking counterexample to this intuition via the seemingly trivial coordinate transform problem, which simply requires learning a mapping between coordinates in (x, y) Cartesian space and one-hot pixel space.
Ranked #887 on Image Classification on ImageNet
no code implementations • 3 Jul 2018 • Piero Molino, Huaixiu Zheng, Yi-Chia Wang
For a company looking to provide delightful user experiences, it is of paramount importance to take care of any customer issues.