6 papers
Correcting Stochastic Update Bias in Preconditioned Language Model Optimizers
Nikhil Nayak, Julia White, Urchade Zaratiana +7
Preconditioned optimizers are central to language model training, but their stochastic update rules are usually treated as direct approximations to population preconditioned descen…
GLiNER2-PII: A Multilingual Model for Personally Identifiable Information Extraction
Urchade Zaratiana, Ash Lewis, George Hurn-Maloney
Reliable detection of personally identifiable information (PII) is increasingly important across modern data-processing systems, yet the task remains difficult: PII spans are heter…
GLiGuard: Schema-Conditioned Classification for LLM Safeguard
Urchade Zaratiana, Mary Newhauser, George Hurn-Maloney +1
Ensuring safe, policy-compliant outputs from large language models requires real-time content moderation that can scale across multiple safety dimensions. However, state-of-the-art…
Pioneer Agent: Continual Improvement of Small Language Models in Production
Dhruv Atreja, Julia White, Nikhil Nayak +5
Small language models are attractive for production deployment due to their low cost, fast inference, and ease of specialization. However, adapting them to a specific task remains…
Beyond Reactivity: Measuring Proactive Problem Solving in LLM Agents
Gil Pasternak, Dheeraj Rajagopal, Julia White +4
LLM-based agents are increasingly moving towards proactivity: rather than awaiting instruction, they exercise agency to anticipate user needs and solve them autonomously. However,…
GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface
Urchade Zaratiana, Gil Pasternak, Oliver Boyd +2
Information extraction (IE) is fundamental to numerous NLP applications, yet existing solutions often require specialized models for different tasks or rely on computationally expe…