26 citations · 53 across the 7 of their papers we have counts for
8 papers
Extracting Dataset Mentions in Forced Displacement and FCV Documents: A Weakly Supervised Framework with LLM-Based Label Refinement
Rafael Macalaba, Aivin V. Solatorio, Patrick Michael Brock +1
Development and humanitarian organizations produce and support surveys, administrative registries, and other data resources to inform research, policy, and operations, yet systemat…
Field Order Should Not Matter: Permutation-Invariant Embedding Model Fine-Tuning for Structured Metadata Retrieval
Aivin V. Solatorio, Olivier Dupriez, Rafael Macalaba
We study retrieval over catalogs of structured metadata, where each record is a small schema whose fields answer different kinds of query. Embedding a record with a text encoder fi…
Proof-Carrying Numbers (PCN): A Protocol for Trustworthy Numeric Answers from LLMs via Claim Verification
Aivin V. Solatorio
Large Language Models (LLMs) as stochastic systems may generate numbers that deviate from available data, a failure known as \emph{numeric hallucination}. Existing safeguards -- re…
Large Language Models and Synthetic Data for Monitoring Dataset Mentions in Research Papers
Aivin V. Solatorio, Rafael Macalaba, James Liounis
Tracking how data is mentioned and used in research papers provides critical insights for improving data discoverability, quality, and production. However, manually identifying and…
Double Jeopardy and Climate Impact in the Use of Large Language Models: Socio-economic Disparities and Reduced Utility for Non-English Speakers
Aivin V. Solatorio, Gabriel Stefanini Vicente, Holly Krambeck +1
Artificial Intelligence (AI), particularly large language models (LLMs), holds the potential to bridge language and information gaps, which can benefit the economies of developing…
GISTEmbed: Guided In-sample Selection of Training Negatives for Text Embedding Fine-tuning
Aivin V. Solatorio
Embedding models are integral to AI applications like semantic search, personalized recommendations, and retrieval augmented generation for LLMs, necessitating high-quality trainin…
GeoFormer: Predicting Human Mobility using Generative Pre-trained Transformer (GPT)
Aivin V. Solatorio
Predicting human mobility holds significant practical value, with applications ranging from enhancing disaster risk planning to simulating epidemic spread. In this paper, we presen…
REaLTabFormer: Generating Realistic Relational and Tabular Data using Transformers
Aivin V. Solatorio, Olivier Dupriez
Tabular data is a common form of organizing data. Multiple models are available to generate synthetic tabular datasets where observations are independent, but few have the ability…