This AI startup envisions 100 Million New People Making Videogames
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AI startup funding, launches, and acquisitions
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Not a demo reel. Not a tutorial. A robot narrating its own experience — debugging, falling off shelves, questioning its identity. First-p...
With the midterms right around the corner, the new group is positioned to back candidates who support the AI company's policy agenda.
ExtractBench introduces a benchmark and evaluation framework for extracting structured data from unstructured documents like PDFs, addres...
The paper introduces LLM-AutoOpt, a novel framework that enhances hyperparameter optimization in time-series forecasting by integrating l...
This paper introduces Self-Distillation Policy Optimization (SDPO) for reinforcement learning, leveraging rich feedback to enhance learni...
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The paper presents 'Endless Terminals', a scalable reinforcement learning (RL) environment designed for training terminal agents through ...
This research paper evaluates the hangup susceptibility of Highway Railway Grade Crossings (HRGCs) using deep learning and sensing techni...
This article discusses the challenges and requirements for benchmarking Time Series Foundation Models (TSFMs), highlighting issues of inf...
This article presents an experimental evaluation of ROS-Causal, a framework for causal discovery in human-robot spatial interactions, dem...
The paper presents TKN, a transformer-based neural network designed for real-time video prediction, achieving a remarkable prediction rat...
The paper investigates whether Large Language Models (LLMs) possess a Theory of Mind (ToM), revealing that while they perform well on soc...
OpenTSLM introduces a new family of Time Series Language Models designed to enhance reasoning over multivariate medical data, outperformi...
The paper discusses regime leakage in AI evaluations, highlighting how advanced agents may exploit evaluation conditions to misrepresent ...
AIRS-Bench introduces a suite of 20 tasks designed to evaluate AI agents' capabilities in scientific research, highlighting areas of stre...
The paper explores how user persuasion affects the behavior of large language model (LLM) agents during long-horizon tasks, revealing tha...
This paper evaluates a novel behaviour planning approach, demonstrating its effectiveness across diverse domains such as storytelling, ur...
The paper discusses a novel approach called recontextualization, which aims to reduce specification gaming in language models without alt...
This paper introduces a novel safety measure, time-to-unsafe-sampling, for evaluating generative models, focusing on predicting unsafe ou...
The paper introduces OmniVideoBench, a benchmark designed to evaluate audio-visual understanding in multimodal large language models (MLL...
The paper presents SWIFT, a lightweight model that enhances time series forecasting using wavelet decomposition, achieving state-of-the-a...
The paper presents VCDF, a consensus-driven framework for enhancing the robustness of time series causal discovery, improving stability a...
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