Test Information Space

Schitt, L. (2021). Mapping global AI governance: a nascent regime in a fragmented landscape

Feldstein, S. (2019). How Artificial Intelligence is Reshaping Repression

CodeTF: One-stop Transformer Library for State-of-the-art Code LLM

Bytes Are All You Need: Transformers Operating Directly On File Bytes

Fine-Tuning Language Models with Just Forward Passes

The Impact of Positional Encoding on Length Generalization in Transformers

SQL-PaLM: Improved Large Language ModelAdaptation for Text-to-SQL

MERT: Acoustic Music Understanding Model with Large-Scale Self-supervised Training

Thought Cloning: Learning to Think while Acting by Imitating Human Thinking

BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks

Human or Not? A Gamified Approach to the Turing Test

StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners

Direct Preference Optimization: Your Language Model is Secretly a Reward Model

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Neuralangelo: High-Fidelity Neural Surface Reconstruction | Research

Large Language Models as Tool Makers

Assessing the impact of regulations and standards on innovation in the field of AI

Stronger Together: on the Articulation of Ethical Charters, Legal Tools, and Technical Documentation in ML

Intriguing Properties of Quantization at Scale

Semiring Reasoning Frameworks in AI and Their Computational Complexity | Journal of Artificial Intelligence Research

Scaling Data-Constrained Language Models

Improving Mathematical Reasoning with Process Supervision

RAPHAEL: Text-to-Image Generation via Large Mixture of Diffusion Paths

Trust within human-machine collectives depends on the perceived consensus about cooperative norms

Meta-MeTTa: an operational semantics for MeTTa

Ultra-low-cost mechanical smartphone attachment for no-calibration blood pressure measurement

Low-threshold, high-resolution, chronically stable intracortical microstimulation by ultraflexible electrodes

AutoML for neuromorphic computing and application-driven co-design: asynchronous, massively parallel optimization of spiking architectures

cuDNN: Efficient Primitives for Deep Learning

Chip Placement with Deep Reinforcement Learning