10 citations
6 papers
LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence
Vlad Vinogradov, Alisa Vinogradova, Dmitrii Radkevich +6
In this paper, we describe and benchmark a competitor-discovery component used within an agentic AI system for fast drug asset due diligence. A competitor-discovery AI agent, given…
SciClaims: An End-to-End Generative System for Biomedical Claim Analysis
Raúl Ortega, José Manuel Gómez-Pérez
We present SciClaims, an interactive web-based system for end-to-end scientific claim analysis in the biomedical domain. Designed for high-stakes use cases such as systematic liter…
Are Compressed Language Models Less Subgroup Robust?
Leonidas Gee, Andrea Zugarini, Novi Quadrianto
To reduce the inference cost of large language models, model compression is increasingly used to create smaller scalable models. However, little is known about their robustness to…
Fast Vocabulary Transfer for Language Model Compression
Leonidas Gee, Andrea Zugarini, Leonardo Rigutini +1
Real-world business applications require a trade-off between language model performance and size. We propose a new method for model compression that relies on vocabulary transfer.…
An energy-based comparative analysis of common approaches to text classification in the Legal domain
Sinan Gultekin, Achille Globo, Andrea Zugarini +2
Most Machine Learning research evaluates the best solutions in terms of performance. However, in the race for the best performing model, many important aspects are often overlooked…
Assessing the Lexico-Semantic Relational Knowledge Captured by Word and Concept Embeddings
Ronald Denaux, Jose Manuel Gomez-Perez
Deep learning currently dominates the benchmarks for various NLP tasks and, at the basis of such systems, words are frequently represented as embeddings --vectors in a low dimensio…