4 citations · 5 across the 6 of their papers we have counts for
7 papers
Characterizing Mamba's Selective Memory using Auto-Encoders
Tamanna Hossain, Robert L. Logan, Ganesh Jagadeesan +3
State space models (SSMs) are a promising alternative to transformers for language modeling because they use fixed memory during inference. However, this fixed memory usage require…
Operationalizing AI for Good: Spotlight on Deployment and Integration of AI Models in Humanitarian Work
Anton Abilov, Ke Zhang, Hemank Lamba +3
Publications in the AI for Good space have tended to focus on the research and model development that can support high-impact applications. However, very few AI for Good papers dis…
Uchaguzi-2022: A Dataset of Citizen Reports on the 2022 Kenyan Election
Roberto Mondini, Neema Kotonya, Robert L. Logan +8
Online reporting platforms have enabled citizens around the world to collectively share their opinions and report in real time on events impacting their local communities. Systemat…
Explain then Rank: Scale Calibration of Neural Rankers Using Natural Language Explanations from LLMs
Puxuan Yu, Daniel Cohen, Hemank Lamba +2
In search settings, calibrating the scores during the ranking process to quantities such as click-through rates or relevance levels enhances a system's usefulness and trustworthine…
Little Giants: Exploring the Potential of Small LLMs as Evaluation Metrics in Summarization in the Eval4NLP 2023 Shared Task
Neema Kotonya, Saran Krishnasamy, Joel Tetreault +1
This paper describes and analyzes our participation in the 2023 Eval4NLP shared task, which focuses on assessing the effectiveness of prompt-based techniques to empower Large Langu…
Harnessing the Power of LLMs: Evaluating Human-AI Text Co-Creation through the Lens of News Headline Generation
Zijian Ding, Alison Smith-Renner, Wenjuan Zhang +2
To explore how humans can best leverage LLMs for writing and how interacting with these models affects feelings of ownership and trust in the writing process, we compared common hu…
An Exploration of Post-Editing Effectiveness in Text Summarization
Vivian Lai, Alison Smith-Renner, Ke Zhang +4
Automatic summarization methods are efficient but can suffer from low quality. In comparison, manual summarization is expensive but produces higher quality. Can humans and AI colla…