Search Results for author: Ilia Markov

Found 22 papers, 6 papers with code

The Role of Context in Detecting the Target of Hate Speech

no code implementations TRAC (COLING) 2022 Ilia Markov, Walter Daelemans

Online hate speech detection is an inherently challenging task that has recently received much attention from the natural language processing community.

Hate Speech Detection Language Modelling

The LiLaH Emotion Lexicon of Croatian, Dutch and Slovene

no code implementations COLING (PEOPLES) 2020 Nikola Ljubešić, Ilia Markov, Darja Fišer, Walter Daelemans

We further showcase the usage of the lexicons by calculating the difference in emotion distributions in texts containing and not containing socially unacceptable discourse, comparing them across four languages (English, Croatian, Dutch, Slovene) and two topics (migrants and LGBT).

Translation

Improving Hate Speech Type and Target Detection with Hateful Metaphor Features

no code implementations NAACL (NLP4IF) 2021 Jens Lemmens, Ilia Markov, Walter Daelemans

We study the usefulness of hateful metaphorsas features for the identification of the type and target of hate speech in Dutch Facebook comments.

Vocal Bursts Type Prediction

Improving Cross-Domain Hate Speech Detection by Reducing the False Positive Rate

no code implementations NAACL (NLP4IF) 2021 Ilia Markov, Walter Daelemans

Hate speech detection is an actively growing field of research with a variety of recently proposed approaches that allowed to push the state-of-the-art results.

Blocking Hate Speech Detection

Exploring Stylometric and Emotion-Based Features for Multilingual Cross-Domain Hate Speech Detection

no code implementations EACL (WASSA) 2021 Ilia Markov, Nikola Ljubešić, Darja Fišer, Walter Daelemans

In this paper, we describe experiments designed to evaluate the impact of stylometric and emotion-based features on hate speech detection: the task of classifying textual content into hate or non-hate speech classes.

Hate Speech Detection

Reasoning about Ambiguous Definite Descriptions

1 code implementation23 Oct 2023 Stefan F. Schouten, Peter Bloem, Ilia Markov, Piek Vossen

But no resources exist to evaluate how well Large Language Models can use explicit reasoning to resolve ambiguity in language.

QUIK: Towards End-to-End 4-Bit Inference on Generative Large Language Models

1 code implementation13 Oct 2023 Saleh Ashkboos, Ilia Markov, Elias Frantar, Tingxuan Zhong, Xincheng Wang, Jie Ren, Torsten Hoefler, Dan Alistarh

We show, for the first time, that the majority of inference computations for large generative models such as LLaMA, OPT, and Falcon can be performed with both weights and activations being cast to 4 bits, in a way that leads to practical speedups, while at the same time maintaining good accuracy.

Computational Efficiency Quantization

Cross-Domain Toxic Spans Detection

1 code implementation16 Jun 2023 Stefan F. Schouten, Baran Barbarestani, Wondimagegnhue Tufa, Piek Vossen, Ilia Markov

Given the dynamic nature of toxic language use, automated methods for detecting toxic spans are likely to encounter distributional shift.

Toxic Spans Detection

Quantized Distributed Training of Large Models with Convergence Guarantees

no code implementations5 Feb 2023 Ilia Markov, Adrian Vladu, Qi Guo, Dan Alistarh

Communication-reduction techniques are a popular way to improve scalability in data-parallel training of deep neural networks (DNNs).

Quantization

L-GreCo: Layerwise-Adaptive Gradient Compression for Efficient and Accurate Deep Learning

1 code implementation31 Oct 2022 Mohammadreza Alimohammadi, Ilia Markov, Elias Frantar, Dan Alistarh

Data-parallel distributed training of deep neural networks (DNN) has gained very widespread adoption, but can still experience communication bottlenecks.

Image Classification Language Modelling +1

CGX: Adaptive System Support for Communication-Efficient Deep Learning

1 code implementation16 Nov 2021 Ilia Markov, Hamidreza Ramezanikebrya, Dan Alistarh

CGX is based on two technical advances: \emph{At the system level}, it relies on a re-developed communication stack for ML frameworks, which provides flexible, highly-efficient support for compressed communication.

A Deep Generative Approach to Native Language Identification

no code implementations COLING 2020 Ehsan Lotfi, Ilia Markov, Walter Daelemans

Native language identification (NLI) {--} identifying the native language (L1) of a person based on his/her writing in the second language (L2) {--} is useful for a variety of purposes, including marketing, security, and educational applications.

BIG-bench Machine Learning Language Modelling +3

Sarcasm Detection Using an Ensemble Approach

no code implementations WS 2020 Jens Lemmens, Ben Burtenshaw, Ehsan Lotfi, Ilia Markov, Walter Daelemans

We present an ensemble approach for the detection of sarcasm in Reddit and Twitter responses in the context of The Second Workshop on Figurative Language Processing held in conjunction with ACL 2020.

Sarcasm Detection

Elastic Consistency: A General Consistency Model for Distributed Stochastic Gradient Descent

no code implementations16 Jan 2020 Giorgi Nadiradze, Ilia Markov, Bapi Chatterjee, Vyacheslav Kungurtsev, Dan Alistarh

Our framework, called elastic consistency enables us to derive convergence bounds for a variety of distributed SGD methods used in practice to train large-scale machine learning models.

BIG-bench Machine Learning

PopSGD: Decentralized Stochastic Gradient Descent in the Population Model

no code implementations25 Sep 2019 Giorgi Nadiradze, Amirmojtaba Sabour, Aditya Sharma, Ilia Markov, Vitaly Aksenov, Dan Alistarh.

We prove that, under standard assumptions, SGD can converge even in this extremely loose, decentralized setting, for both convex and non-convex objectives.

Distributed Optimization Scheduling

Anglicized Words and Misspelled Cognates in Native Language Identification

no code implementations WS 2019 Ilia Markov, Vivi Nastase, Carlo Strapparava

In this paper, we present experiments that estimate the impact of specific lexical choices of people writing in a second language (L2).

Native Language Identification

The Role of Emotions in Native Language Identification

no code implementations WS 2018 Ilia Markov, Vivi Nastase, Carlo Strapparava, Grigori Sidorov

We explore the hypothesis that emotion is one of the dimensions of language that surfaces from the native language into a second language.

Deception Detection Native Language Identification +1

Punctuation as Native Language Interference

no code implementations COLING 2018 Ilia Markov, Vivi Nastase, Carlo Strapparava

In this paper, we describe experiments designed to explore and evaluate the impact of punctuation marks on the task of native language identification.

Classification Cross-corpus +3

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