1 code implementation • 31 May 2025 • Pardis Sadat Zahraei, Ali Emami
This work emphasizes the need for targeted approaches to gender and semantic coherence in machine translation, particularly for genderless languages, contributing to more equitable and accurate translation systems.
no code implementations • 29 Apr 2025 • Tyler McDonald, Ali Emami
Knowledge distillation allows smaller neural networks to emulate the performance of larger, teacher models with reduced computational demands.
no code implementations • 10 Apr 2025 • Sher Badshah, Ali Emami, Hassan Sajjad
TALE enhances the reliability of LLM evaluations in real-world, dynamic scenarios without relying on static references.
1 code implementation • 7 Feb 2025 • Sangmitra Madhusudan, Robert Morabito, Skye Reid, Nikta Gohari Sadr, Ali Emami
Our findings indicate that LLMs trained on decade-specific books manifest biases reflective of their times, with both gradual trends and notable shifts.
no code implementations • 5 Feb 2025 • Nikta Gohari Sadr, Sangmitra Madhusudan, Ali Emami
For instance, while both 'step-by-step' and 'think' show high ZIP scores, which one is more influential depends on the model and task.
1 code implementation • 2 Dec 2024 • Tyler McDonald, Anthony Colosimo, Yifeng Li, Ali Emami
As prompt engineering research rapidly evolves, evaluations beyond accuracy are crucial for developing cost-effective techniques.
no code implementations • 2 Dec 2024 • Angel Yahir Loredo Lopez, Tyler McDonald, Ali Emami
Large Language Models (LLMs) have shown impressive performance on various benchmarks, yet their ability to engage in deliberate reasoning remains questionable.
1 code implementation • 20 Sep 2024 • Robert Morabito, Sangmitra Madhusudan, Tyler McDonald, Ali Emami
Mitigating explicit and implicit biases in Large Language Models (LLMs) has become a critical focus in the field of natural language processing.
no code implementations • 20 Sep 2024 • Sarfaroz Yunusov, Hamza Sidat, Ali Emami
This study explores the effectiveness of Large Language Models (LLMs) in creating personalized "mirror stories" that reflect and resonate with individual readers' identities, addressing the significant lack of diversity in literature.
no code implementations • 25 May 2024 • Brendan Park, Madeline Janecek, Naser Ezzati-Jivan, Yifeng Li, Ali Emami
Utilizing GPT-4 for prompt generation and Diffusion Attentive Attribution Maps (DAAM) for heatmap analysis, we propose a novel evaluation framework that isolates the models' ability in pronoun disambiguation from other visual processing challenges.
1 code implementation • 25 May 2024 • Abhishek Kumar, Robert Morabito, Sanzhar Umbet, Jad Kabbara, Ali Emami
Using various datasets and prompting techniques that encourage model introspection, we probe the alignment between models' internal and expressed confidence.
1 code implementation • 23 May 2024 • Abhishek Kumar, Sarfaroz Yunusov, Ali Emami
Research on Large Language Models (LLMs) has often neglected subtle biases that, although less apparent, can significantly influence the models' outputs toward particular social narratives.
no code implementations • 20 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.
1 code implementation • 31 Jan 2024 • Pardis Sadat Zahraei, Ali Emami
The Winograd Schema Challenge (WSC) serves as a prominent benchmark for evaluating machine understanding.
1 code implementation • 23 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.
1 code implementation • 15 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.
no code implementations • 21 Feb 2022 • Ghazaleh Ghorbanzadeh, Zahra Nabizadeh, Nader Karimi, Pejman Khadivi, Ali Emami, Shadrokh Samavi
The proposed method accelerates the convergence of the genetic algorithm and increases the system's performance.
no code implementations • 23 Jan 2022 • Darren Abramson, Ali Emami
We identify a practical cost for our method and model: high GPU-time for natural language evaluation.
no code implementations • 29 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.
no code implementations • ACL 2021 • Ali Emami, Ian Porada, Alexandra Olteanu, Kaheer Suleman, Adam Trischler, Jackie Chi Kit Cheung
A false contract is more likely to be rejected than a contract is, yet a false key is less likely than a key to open doors.
1 code implementation • 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).
no code implementations • 24 Jul 2020 • Ghazale Ghorbanzade, Zahra Nabizadeh-ShahreBabak, Shadrokh Samavi, Nader Karimi, Ali Emami, Pejman Khadivi
Reduction of the number of channels could reduce the complexity of brain-computer-interface devices.
no code implementations • 5 Feb 2020 • Zahra Sobhaninia, Safiyeh Rezaei, Nader Karimi, Ali Emami, Shadrokh Samavi
Intracranial tumors are groups of cells that usually grow uncontrollably.
no code implementations • 3 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.
no code implementations • 3 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.
no code implementations • 31 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.
no code implementations • 31 Aug 2019 • Safiyeh Rezaei, Ali Emami, Hamidreza Zarrabi, Shima Rafiei, Kayvan Najarian, Nader Karimi, Shadrokh Samavi, S. M. Reza Soroushmehr
Histopathology images contain essential information for medical diagnosis and prognosis of cancerous disease.
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.
Ranked #36 on
Coreference Resolution
on Winograd Schema Challenge
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.
1 code implementation • 16 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.
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.
Ranked #65 on
Coreference Resolution
on Winograd Schema Challenge
no code implementations • 20 Sep 2018 • Zahra Sobhaninia, Safiyeh Rezaei, Alireza Noroozi, Mehdi Ahmadi, Hamidreza Zarrabi, Nader Karimi, Ali Emami, Shadrokh Samavi
The effect of using separate networks for segmentation of MR images is evaluated by comparing the results with a single network.
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).
no code implementations • 23 Feb 2018 • Alireza Norouzi, Ali Emami, S. M. Reza Soroushmehr, Nader Karimi, Shadrokh Samavi, Kayvan Najarian
Deep neural networks have shown great achievements in solving complex problems.
no code implementations • 21 Feb 2018 • Mahdi Ahmadi, Ali Emami, Mohsen Hajabdollahi, S. M. Reza Soroushmehr, Nader Karimi, Shadrokh Samavi, Kayvan Najarian
By increasing the volume of telemedicine information, the need for medical image compression has become more important.
no code implementations • 21 Feb 2018 • Atefe Rajaeefar, Ali Emami, S. M. Reza Soroushmehr, Nader Karimi, Shadrokh Samavi, Kayvan Najarian
Recent advances in capsule endoscopy systems have introduced new methods and capabilities.