5 citations · 10 across the 10 of their papers we have counts for
14 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…
CEHA: A Dataset of Conflict Events in the Horn of Africa
Rui Bai, Di Lu, Shihao Ran +5
Natural Language Processing (NLP) of news articles can play an important role in understanding the dynamics and causes of violent conflict. Despite the availability of datasets cat…
HumVI: A Multilingual Dataset for Detecting Violent Incidents Impacting Humanitarian Aid
Hemank Lamba, Anton Abilov, Ke Zhang +8
Humanitarian organizations can enhance their effectiveness by analyzing data to discover trends, gather aggregated insights, manage their security risks, support decision-making, a…
Dissecting users' needs for search result explanations
Prerna Juneja, Wenjuan Zhang, Alison Marie Smith-Renner +3
There is a growing demand for transparency in search engines to understand how search results are curated and to enhance users' trust. Prior research has introduced search result e…
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…