Search Results for author: Ali Emami

Found 24 papers, 6 papers with code

EvoGrad: A Dynamic Take on the Winograd Schema Challenge with Human Adversaries

no code implementations20 Feb 2024 Jing Han Sun, Ali Emami

Our results emphasize the challenge posed by EvoGrad: Even the best performing LLM, GPT-3. 5, achieves an accuracy of 65. 0% with an average error depth of 7. 2, a stark contrast to human performance of 92.

Common Sense Reasoning coreference-resolution

WSC+: Enhancing The Winograd Schema Challenge Using Tree-of-Experts

1 code implementation31 Jan 2024 Pardis Sadat Zahraei, Ali Emami

The Winograd Schema Challenge (WSC) serves as a prominent benchmark for evaluating machine understanding.


Debiasing should be Good and Bad: Measuring the Consistency of Debiasing Techniques in Language Models

1 code implementation23 May 2023 Robert Morabito, Jad Kabbara, Ali Emami

Debiasing methods that seek to mitigate the tendency of Language Models (LMs) to occasionally output toxic or inappropriate text have recently gained traction.

Dynamic-Pix2Pix: Noise Injected cGAN for Modeling Input and Target Domain Joint Distributions with Limited Training Data

1 code implementation15 Nov 2022 Mohammadreza Naderi, Nader Karimi, Ali Emami, Shahram Shirani, Shadrokh Samavi

Helping the cGAN learn the target distribution from noise input results in a better model generalization during the test time and allows the model to fit almost perfectly to the target domain distribution.

Domain Generalization

An Application of Pseudo-Log-Likelihoods to Natural Language Scoring

no code implementations23 Jan 2022 Darren Abramson, Ali Emami

We identify a practical cost for our method and model: high GPU-time for natural language evaluation.

Language Modelling Text Generation +1

Not-so fine-tuning: Measures of Common Sense for Language Models

no code implementations29 Sep 2021 Darren Abramson, Ali Emami

Language models built using semi-supervised machine learning on large corpora of natural language have very quickly enveloped the fields of natural language generation and understanding.

Common Sense Reasoning Language Modelling +1

An Analysis of Dataset Overlap on Winograd-Style Tasks

no code implementations COLING 2020 Ali Emami, Adam Trischler, Kaheer Suleman, Jackie Chi Kit Cheung

The Winograd Schema Challenge (WSC) and variants inspired by it have become important benchmarks for common-sense reasoning (CSR).

Common Sense Reasoning Test

Localization of Fetal Head in Ultrasound Images by Multiscale View and Deep Neural Networks

no code implementations3 Nov 2019 Zahra Sobhaninia, Ali Emami, Nader Karimi, Shadrokh Samavi

One of the routine examinations that are used for prenatal care in many countries is ultrasound imaging.

Gland Segmentation in Histopathological Images by Deep Neural Network

no code implementations3 Nov 2019 Safiye Rezaei, Ali Emami, Nader Karimi, Shadrokh Samavi

Histology method is vital in the diagnosis and prognosis of cancers and many other diseases.

Segmentation Test

Fetal Ultrasound Image Segmentation for Measuring Biometric Parameters Using Multi-Task Deep Learning

no code implementations31 Aug 2019 Zahra Sobhaninia, Shima Rafiei, Ali Emami, Nader Karimi, Kayvan Najarian, Shadrokh Samavi, S. M. Reza Soroushmehr

Ultrasound imaging is a standard examination during pregnancy that can be used for measuring specific biometric parameters towards prenatal diagnosis and estimating gestational age.

Image Segmentation Segmentation +1

How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG

1 code implementation IJCNLP 2019 Paul Trichelair, Ali Emami, Adam Trischler, Kaheer Suleman, Jackie Chi Kit Cheung

Recent studies have significantly improved the state-of-the-art on common-sense reasoning (CSR) benchmarks like the Winograd Schema Challenge (WSC) and SWAG.

Common Sense Reasoning

The Knowref Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution

1 code implementation ACL 2019 Ali Emami, Paul Trichelair, Adam Trischler, Kaheer Suleman, Hannes Schulz, Jackie Chi Kit Cheung

To explain this performance gap, we show empirically that state-of-the art models often fail to capture context, instead relying on the gender or number of candidate antecedents to make a decision.

Common Sense Reasoning coreference-resolution +2

ReDMark: Framework for Residual Diffusion Watermarking on Deep Networks

1 code implementation16 Oct 2018 Mahdi Ahmadi, Alireza Norouzi, S. M. Reza Soroushmehr, Nader Karimi, Kayvan Najarian, Shadrokh Samavi, Ali Emami

Due to the rapid growth of machine learning tools and specifically deep networks in various computer vision and image processing areas, application of Convolutional Neural Networks for watermarking have recently emerged.

A Knowledge Hunting Framework for Common Sense Reasoning

no code implementations EMNLP 2018 Ali Emami, Noelia De La Cruz, Adam Trischler, Kaheer Suleman, Jackie Chi Kit Cheung

We introduce an automatic system that achieves state-of-the-art results on the Winograd Schema Challenge (WSC), a common sense reasoning task that requires diverse, complex forms of inference and knowledge.

Common Sense Reasoning

A Generalized Knowledge Hunting Framework for the Winograd Schema Challenge

no code implementations NAACL 2018 Ali Emami, Adam Trischler, Kaheer Suleman, Jackie Chi Kit Cheung

We introduce an automatic system that performs well on two common-sense reasoning tasks, the Winograd Schema Challenge (WSC) and the Choice of Plausible Alternatives (COPA).

Common Sense Reasoning Coreference Resolution +1

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