470 citations · 632 across the 24 of their papers we have counts for
26 papers
OpenAI GPT-5 System Card
Aaditya Singh, Adam Fry, Adam Perelman +483
This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers most questions, a deeper reason…
Competitive Programming with Large Reasoning Models
OpenAI, :, Ahmed El-Kishky +23
We show that reinforcement learning applied to large language models (LLMs) significantly boosts performance on complex coding and reasoning tasks. Additionally, we compare two gen…
OpenAI o1 System Card
OpenAI, :, Aaron Jaech +261
The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. These advanced reasoning capabilities provide new avenues for improving the…
URL-BERT: Training Webpage Representations via Social Media Engagements
Ayesha Qamar, Chetan Verma, Ahmed El-Kishky +3
Understanding and representing webpages is crucial to online social networks where users may share and engage with URLs. Common language model (LM) encoders such as BERT can be use…
NTULM: Enriching Social Media Text Representations with Non-Textual Units
Jinning Li, Shubhanshu Mishra, Ahmed El-Kishky +2
On social media, additional context is often present in the form of annotations and meta-data such as the post's author, mentions, Hashtags, and hyperlinks. We refer to these annot…
MiCRO: Multi-interest Candidate Retrieval Online
Frank Portman, Stephen Ragain, Ahmed El-Kishky
Providing personalized recommendations in an environment where items exhibit ephemerality and temporal relevancy (e.g. in social media) presents a few unique challenges: (1) induct…
TwHIN-BERT: A Socially-Enriched Pre-trained Language Model for Multilingual Tweet Representations at Twitter
Xinyang Zhang, Yury Malkov, Omar Florez +4
Pre-trained language models (PLMs) are fundamental for natural language processing applications. Most existing PLMs are not tailored to the noisy user-generated text on social medi…
Non-Parametric Temporal Adaptation for Social Media Topic Classification
Fatemehsadat Mireshghallah, Nikolai Vogler, Junxian He +3
User-generated social media data is constantly changing as new trends influence online discussion and personal information is deleted due to privacy concerns. However, most current…
kNN-Embed: Locally Smoothed Embedding Mixtures For Multi-interest Candidate Retrieval
Ahmed El-Kishky, Thomas Markovich, Kenny Leung +3
Candidate retrieval is the first stage in recommendation systems, where a light-weight system is used to retrieve potentially relevant items for an input user. These candidate item…
TwHIN: Embedding the Twitter Heterogeneous Information Network for Personalized Recommendation
Ahmed El-Kishky, Thomas Markovich, Serim Park +8
Social networks, such as Twitter, form a heterogeneous information network (HIN) where nodes represent domain entities (e.g., user, content, advertiser, etc.) and edges represent o…
Learning Stance Embeddings from Signed Social Graphs
John Pougué-Biyong, Akshay Gupta, Aria Haghighi +1
A key challenge in social network analysis is understanding the position, or stance, of people in the graph on a large set of topics. While past work has modeled (dis)agreement in…
Classification-based Quality Estimation: Small and Efficient Models for Real-world Applications
Shuo Sun, Ahmed El-Kishky, Vishrav Chaudhary +3
Sentence-level Quality estimation (QE) of machine translation is traditionally formulated as a regression task, and the performance of QE models is typically measured by Pearson co…
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation
Jun Wang, Chang Xu, Francisco Guzman +3
Mistranslated numbers have the potential to cause serious effects, such as financial loss or medical misinformation. In this work we develop comprehensive assessments of the robust…
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning
Jun Wang, Chang Xu, Francisco Guzman +4
Neural machine translation systems are known to be vulnerable to adversarial test inputs, however, as we show in this paper, these systems are also vulnerable to training attacks.…
Adapting High-resource NMT Models to Translate Low-resource Related Languages without Parallel Data
Wei-Jen Ko, Ahmed El-Kishky, Adithya Renduchintala +6
The scarcity of parallel data is a major obstacle for training high-quality machine translation systems for low-resource languages. Fortunately, some low-resource languages are lin…
XLEnt: Mining a Large Cross-lingual Entity Dataset with Lexical-Semantic-Phonetic Word Alignment
Ahmed El-Kishky, Adithya Renduchintala, James Cross +2
Cross-lingual named-entity lexica are an important resource to multilingual NLP tasks such as machine translation and cross-lingual wikification. While knowledge bases contain a la…
Quality Estimation without Human-labeled Data
Yi-Lin Tuan, Ahmed El-Kishky, Adithya Renduchintala +3
Quality estimation aims to measure the quality of translated content without access to a reference translation. This is crucial for machine translation systems in real-world scenar…
Beyond English-Centric Multilingual Machine Translation
Angela Fan, Shruti Bhosale, Holger Schwenk +14
Existing work in translation demonstrated the potential of massively multilingual machine translation by training a single model able to translate between any pair of languages. Ho…
Massively Multilingual Document Alignment with Cross-lingual Sentence-Mover's Distance
Ahmed El-Kishky, Francisco Guzmán
Document alignment aims to identify pairs of documents in two distinct languages that are of comparable content or translations of each other. Such aligned data can be used for a v…
Mining News Events from Comparable News Corpora: A Multi-Attribute Proximity Network Modeling Approach
Hyungsul Kim, Ahmed El-Kishky, Xiang Ren +1
We present ProxiModel, a novel event mining framework for extracting high-quality structured event knowledge from large, redundant, and noisy news data sources. The proposed model…
CCAligned: A Massive Collection of Cross-Lingual Web-Document Pairs
Ahmed El-Kishky, Vishrav Chaudhary, Francisco Guzman +1
Cross-lingual document alignment aims to identify pairs of documents in two distinct languages that are of comparable content or translations of each other. In this paper, we explo…
Leveraging Pretrained Image Classifiers for Language-Based Segmentation
David Golub, Ahmed El-Kishky, Roberto Martín-Martín
Current semantic segmentation models cannot easily generalize to new object classes unseen during train time: they require additional annotated images and retraining. We propose a…
Facebook AI's WAT19 Myanmar-English Translation Task Submission
Peng-Jen Chen, Jiajun Shen, Matt Le +5
This paper describes Facebook AI's submission to the WAT 2019 Myanmar-English translation task. Our baseline systems are BPE-based transformer models. We explore methods to leverag…
Parsimonious Morpheme Segmentation with an Application to Enriching Word Embeddings
Ahmed El-Kishky, Frank Xu, Aston Zhang +1
Traditionally, many text-mining tasks treat individual word-tokens as the finest meaningful semantic granularity. However, in many languages and specialized corpora, words are comp…