Search Results for author:
Found 15 papers, 7 papers with code
Segment-Level Diffusion: A Framework for Controllable Long-Form Generation with Diffusion Language Models
Diffusion models have shown promise in text generation but often struggle with generating long, coherent, and contextually accurate text.
The Automated Verification of Textual Claims (AVeriTeC) Shared Task
The Automated Verification of Textual Claims (AVeriTeC) shared task asks participants to retrieve evidence and predict veracity for real-world claims checked by fact-checkers.
SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages
Southeast Asia (SEA) is a region rich in linguistic diversity and cultural variety, with over 1, 300 indigenous languages and a population of 671 million people.
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
Visual Question Answering (VQA) is an important task in multimodal AI, and it is often used to test the ability of vision-language models to understand and reason on knowledge present in both visual and textual data.
SemEval-2024 Task 8: Multidomain, Multimodel and Multilingual Machine-Generated Text Detection
The task attracted a large number of participants: subtask A monolingual (126), subtask A multilingual (59), subtask B (70), and subtask C (30).
PRobELM: Plausibility Ranking Evaluation for Language Models
This paper introduces PRobELM (Plausibility Ranking Evaluation for Language Models), a benchmark designed to assess language models' ability to discern more plausible from less plausible scenarios through their parametric knowledge.
Towards Knowledge-Grounded Natural Language Understanding and Generation
This thesis investigates how natural language understanding and generation with transformer models can benefit from grounding the models with knowledge representations and addresses the following key research questions: (i) Can knowledge of entities extend its benefits beyond entity-centric tasks, such as entity linking?
Inducing Generalization across Languages and Tasks using Featurized Low-Rank Mixtures
By composing feature-specific parameters for each dataset, FLix can accommodate diverse dataset mixtures and generalize better to unseen datasets.
Low-Rank Adaptation for Multilingual Summarization: An Empirical Study
Although the advancements of pre-trained Large Language Models have significantly accelerated recent progress in NLP, their ever-increasing size poses significant challenges for conventional fine-tuning, especially in memory-intensive tasks.
M4: Multi-generator, Multi-domain, and Multi-lingual Black-Box Machine-Generated Text Detection
These results show that the problem is far from solved and that there is a lot of room for improvement.
LLM-powered Data Augmentation for Enhanced Cross-lingual Performance
This paper explores the potential of leveraging Large Language Models (LLMs) for data augmentation in multilingual commonsense reasoning datasets where the available training data is extremely limited.
WebIE: Faithful and Robust Information Extraction on the Web
We evaluate the in-domain, out-of-domain, and zero-shot cross-lingual performance of generative IE models and find models trained on WebIE show better generalisability.
Towards a Unified Model for Generating Answers and Explanations in Visual Question Answering
The field of visual question answering (VQA) has recently seen a surge in research focused on providing explanations for predicted answers.
EntityCS: Improving Zero-Shot Cross-lingual Transfer with Entity-Centric Code Switching
We use Wikidata and English Wikipedia to construct an entity-centric CS corpus by switching entities to their counterparts in other languages.
Evaluation of Fake News Detection with Knowledge-Enhanced Language Models
The predominant state-of-the-art approaches are based on fine-tuning PLMs on labelled fake news datasets.
