573 citations · 1.5k across the 13 of their papers we have counts for
14 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…
GPT-4o System Card
OpenAI, :, Aaron Hurst +416
GPT-4o is an autoregressive omni model that accepts as input any combination of text, audio, image, and video, and generates any combination of text, audio, and image outputs. It's…
Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions
Angana Borah, Rada Mihalcea
As Large Language Models (LLMs) continue to evolve, they are increasingly being employed in numerous studies to simulate societies and execute diverse social tasks. However, LLMs a…
GPT-4 Technical Report
OpenAI, Josh Achiam, Steven Adler +278
We report the development of GPT-4, a large-scale, multimodal model which can accept image and text inputs and produce text outputs. While less capable than humans in many real-wor…
Generate, Annotate, and Learn: NLP with Synthetic Text
Xuanli He, Islam Nassar, Jamie Kiros +2
This paper studies the use of language models as a source of synthetic unlabeled text for NLP. We formulate a general framework called ``generate, annotate, and learn (GAL)'' to ta…
Multichannel Generative Language Model: Learning All Possible Factorizations Within and Across Channels
Harris Chan, Jamie Kiros, William Chan
A channel corresponds to a viewpoint or transformation of an underlying meaning. A pair of parallel sentences in English and French express the same underlying meaning, but through…
Contextual Lensing of Universal Sentence Representations
Jamie Kiros
What makes a universal sentence encoder universal? The notion of a generic encoder of text appears to be at odds with the inherent contextualization and non-permanence of language…
An Empirical Study of Generation Order for Machine Translation
William Chan, Mitchell Stern, Jamie Kiros +1
In this work, we present an empirical study of generation order for machine translation. Building on recent advances in insertion-based modeling, we first introduce a soft order-re…
Graph Normalizing Flows
Jenny Liu, Aviral Kumar, Jimmy Ba +2
We introduce graph normalizing flows: a new, reversible graph neural network model for prediction and generation. On supervised tasks, graph normalizing flows perform similarly to…
DOM-Q-NET: Grounded RL on Structured Language
Sheng Jia, Jamie Kiros, Jimmy Ba
Building agents to interact with the web would allow for significant improvements in knowledge understanding and representation learning. However, web navigation tasks are difficul…
ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning
Harris Chan, Yuhuai Wu, Jamie Kiros +2
Sparse reward is one of the most challenging problems in reinforcement learning (RL). Hindsight Experience Replay (HER) attempts to address this issue by converting a failed experi…
Insertion Transformer: Flexible Sequence Generation via Insertion Operations
Mitchell Stern, William Chan, Jamie Kiros +1
We present the Insertion Transformer, an iterative, partially autoregressive model for sequence generation based on insertion operations. Unlike typical autoregressive models which…
VSE++: Improving Visual-Semantic Embeddings with Hard Negatives
Fartash Faghri, David J. Fleet, Jamie Ryan Kiros +1
We present a new technique for learning visual-semantic embeddings for cross-modal retrieval. Inspired by hard negative mining, the use of hard negatives in structured prediction,…
Layer Normalization
Jimmy Lei Ba, Jamie Ryan Kiros, Geoffrey E. Hinton
Training state-of-the-art, deep neural networks is computationally expensive. One way to reduce the training time is to normalize the activities of the neurons. A recently introduc…