Search Results for author:
Found 11 papers, 9 papers with code
Benchmarking Meta-embeddings: What Works and What Does Not
In the last few years, several methods have been proposed to build meta-embeddings.
Data Contamination Report from the 2024 CONDA Shared Task
The workshop fostered a shared task to collect evidence on data contamination in current available datasets and models.
Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain
While these LLMs display competitive performance on automated medical texts benchmarks, they have been pre-trained and evaluated with a focus on a single language (English mostly).
NoticIA: A Clickbait Article Summarization Dataset in Spanish
We present NoticIA, a dataset consisting of 850 Spanish news articles featuring prominent clickbait headlines, each paired with high-quality, single-sentence generative summarizations written by humans.
NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark
In this position paper, we argue that the classical evaluation on Natural Language Processing (NLP) tasks using annotated benchmarks is in trouble.
This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models
We have used our dataset with the largest available open LLMs in a zero-shot approach to grasp their generalization and inference capability and we have also fine-tuned some of the models to assess whether the understanding of negation can be trained.
GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction
In this paper, we propose GoLLIE (Guideline-following Large Language Model for IE), a model able to improve zero-shot results on unseen IE tasks by virtue of being fine-tuned to comply with annotation guidelines.
Ranked #1 on
Zero-shot Named Entity Recognition (NER)
on HarveyNER
(using extra training data)
IXA/Cogcomp at SemEval-2023 Task 2: Context-enriched Multilingual Named Entity Recognition using Knowledge Bases
Named Entity Recognition (NER) is a core natural language processing task in which pre-trained language models have shown remarkable performance.
Multilingual Named Entity Recognition
named-entity-recognition
+4
T-Projection: High Quality Annotation Projection for Sequence Labeling Tasks
In the absence of readily available labeled data for a given sequence labeling task and language, annotation projection has been proposed as one of the possible strategies to automatically generate annotated data.
Ranked #1 on
Cross-Lingual NER
on MasakhaNER2.0
(Hausa metric)
Model and Data Transfer for Cross-Lingual Sequence Labelling in Zero-Resource Settings
Zero-resource cross-lingual transfer approaches aim to apply supervised models from a source language to unlabelled target languages.
Ranked #1 on
Cross-Lingual NER
on CoNLL Spanish
A Common Semantic Space for Monolingual and Cross-Lingual Meta-Embeddings
This paper presents a new technique for creating monolingual and cross-lingual meta-embeddings.
