7k citations
- University of California, Santa BarbaraUS109 papers
- Microsoft Research (United Kingdom)GB47 papers
- ETH ZurichCH46 papers
- University of California, BerkeleyUS45 papers
- University of Maryland, College ParkUS43 papers
- Carnegie Mellon UniversityUS41 papers
- Stanford UniversityUS39 papers
- University of WashingtonUS36 papers
- Cornell UniversityUS32 papers
- Princeton UniversityUS31 papers
- California Institute of TechnologyUS28 papers
- Georgia Institute of TechnologyUS24 papers
48 papers · 1 filter
Preliminary WMT24 Ranking of General MT Systems and LLMs
Tom Kocmi, Eleftherios Avramidis, Rachel Bawden +18
This is the preliminary ranking of WMT24 General MT systems based on automatic metrics. The official ranking will be a human evaluation, which is superior to the automatic ranking…
Grounding and Evaluation for Large Language Models: Practical Challenges and Lessons Learned (Survey)
Krishnaram Kenthapadi, Mehrnoosh Sameki, Ankur Taly
With the ongoing rapid adoption of Artificial Intelligence (AI)-based systems in high-stakes domains, ensuring the trustworthiness, safety, and observability of these systems has b…
Examining risks of racial biases in NLP tools for child protective services
Anjalie Field, Amanda Coston, Nupoor Gandhi +4
Although much literature has established the presence of demographic bias in natural language processing (NLP) models, most work relies on curated bias metrics that may not be refl…
Supporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Coding
Ziang Xiao, Xingdi Yuan, Q. Vera Liao +2
Qualitative analysis of textual contents unpacks rich and valuable information by assigning labels to the data. However, this process is often labor-intensive, particularly when wo…
Sequence-level self-learning with multiple hypotheses
Kenichi Kumatani, Dimitrios Dimitriadis, Yashesh Gaur +4
In this work, we develop new self-learning techniques with an attention-based sequence-to-sequence (seq2seq) model for automatic speech recognition (ASR). For untranscribed speech…
Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP
Trapit Bansal, Karthick Gunasekaran, Tong Wang +2
Meta-learning considers the problem of learning an efficient learning process that can leverage its past experience to accurately solve new tasks. However, the efficacy of meta-lea…