8 papers
Dynamic LLM Routers are Often Misguided
Sam Wang, Julia White, Sahibzada Allahyar +3
Dynamic LLM routers promise to cut inference costs by sending each query to the cheapest model that can answer it correctly. We analyze six commercial routers across 14 settings on…
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…
EnriCo: Enriched Representation and Globally Constrained Inference for Entity and Relation Extraction
Urchade Zaratiana, Nadi Tomeh, Yann Dauxais +2
Joint entity and relation extraction plays a pivotal role in various applications, notably in the construction of knowledge graphs. Despite recent progress, existing approaches oft…
GraphER: A Structure-aware Text-to-Graph Model for Entity and Relation Extraction
Urchade Zaratiana, Nadi Tomeh, Niama El Khbir +2
Information extraction (IE) is an important task in Natural Language Processing (NLP), involving the extraction of named entities and their relationships from unstructured text. In…
An Autoregressive Text-to-Graph Framework for Joint Entity and Relation Extraction
Urchade Zaratiana, Nadi Tomeh, Pierre Holat +1
In this paper, we propose a novel method for joint entity and relation extraction from unstructured text by framing it as a conditional sequence generation problem. In contrast to…