Search Results for author:
Found 8 papers, 3 papers with code
HYPHEN: Hyperbolic Hawkes Attention For Text Streams
Analyzing the temporal sequence of texts from sources such as social media, news, and parliamentary debates is a challenging problem as it exhibits time-varying scale-free properties and fine-grained timing irregularities.
Contamination Report for Multilingual Benchmarks
Benchmark contamination refers to the presence of test datasets in Large Language Model (LLM) pre-training or post-training data.
Scaling Laws for Multilingual Language Models
We propose a novel scaling law for general-purpose decoder-only language models (LMs) trained on multilingual data, tackling the problem of balancing languages during multilingual pretraining.
sPhinX: Sample Efficient Multilingual Instruction Fine-Tuning Through N-shot Guided Prompting
In order to address this, we introduce a novel recipe for creating a multilingual synthetic instruction tuning dataset, sPhinX, which is created by selectively translating instruction response pairs from English into 50 languages.
SemEval-2024 Task 1: Semantic Textual Relatedness for African and Asian Languages
We present the first shared task on Semantic Textual Relatedness (STR).
DOSA: A Dataset of Social Artifacts from Different Indian Geographical Subcultures
Generative models are increasingly being used in various applications, such as text generation, commonsense reasoning, and question-answering.
SemRel2024: A Collection of Semantic Textual Relatedness Datasets for 13 Languages
Exploring and quantifying semantic relatedness is central to representing language and holds significant implications across various NLP tasks.
MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks
We also perform a study on data contamination and find that several models are likely to be contaminated with multilingual evaluation benchmarks, necessitating approaches to detect and handle contamination while assessing the multilingual performance of LLMs.
