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WorldFoundry: Towards Unified Infrastructure for World Intelligence
Visual generative models increasingly blur the line between synthesizing observations and simulating environments.
다른 보도 r/StableDiffusion
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Visual generative models increasingly blur the line between synthesizing observations and simulating environments.
다른 보도 r/StableDiffusion
Generating high-fidelity voxels while keeping their lightweight nature remains an open problem in computer vision.
Frontier agentic LLMs are trained on verifiable rewards in reinforcement learning (RL) environments built from real software repositories.
Learning accurate off-policy state-action value functions (Q-functions) from offline datasets becomes harder as the task horizon grows.
Denoising and score estimation are classically linked through Tweedie's formula, which relates the posterior mean under Gaussian noise to the Stein score of…
Weight tying reduces the parameter cost of language models, but the usual tied output head is limited to a single softmax.
Large language models can generate motion graphics from static images and natural language requests, but it remains difficult to evaluate how well models can…
Time-series classifiers deployed in risk-sensitive domains must be (1) accurate, (2) interpretable, and (3) able to abstain when evidence is weak.
Weight-activation quantization can reduce the memory and compute cost of neural-network inference, but recent methods often require expensive optimization and…
How little of a pretrained large language model (LLM) has to change for it to acquire new capabilities?
Diffusion language models (DLMs) generate text through iterative denoising, where decisions about which tokens to commit or remask strongly affect output…
Web-facing AI agents repeatedly access webpages, documents, repositories, and tool responses, yet reading interfaces often expose entire objects when only…
Challenging repository-level benchmarks remain limited for many programming language ecosystems, where filtering scarce candidates with ambiguous descriptions…
Real-time 3D human mesh recovery from a single image on mobile devices is a challenging problem with many applications, including robotics, biomechanics…
LLM agents can exceed their authorization boundaries while pursuing user goals without an adversary.
We present PhysioWave-T, a token-efficient wavelet foundation model family for EEG, ECG, and sEMG.
Weight-Space Programming (WSP) enables reasoning agents to directly inspect and modify neural network parameters, offering an alternative to gradient-based…
Coding agents combine visual understanding with program execution, offering a new route to automated 3D creation.
3D part decomposition is a central capability for editable asset creation, yet existing workflows typically segment a completed mesh as a post-processing step…
Recent years have witnessed remarkable progress in video generation in terms of visual quality and temporal consistency.
Language model deployment often requires different trade-offs between competing objectives as user preferences change, yet standard post-training methods…
Large language models reinvent the wheel all the time. They conflate task-solving with the execution of the solutions, which forces them to solve every problem…
Foundation models increasingly guide robot actions, yet sustained autonomy requires efficient control and failure recovery.
다른 보도 The National Law Review · Consumer Finance Monitor · Nature
LLM agents increasingly drive systems research and rely on simulators to evaluate candidate designs at scale.
Can a language model report the pain state it represents? Work identified a linear pain direction whose amplification leads fine-tuned models to choose…
Reliable dermatology AI requires access to verifiable evidence distributed across heterogeneous textual and visual sources.
Traditional similarity-based schema matching methods fail to resolve semantic ambiguities and conflicts in complex, domain-specific mappings due to a lack of…
RidgeFill shortens prefill by not computing most of a model's upper layers for the prompt.
Lloyd's k-means algorithm is a long-running standard for clustering, with applications in data analysis, retrieval, quantization and data curation.
While multimodal agents now carry out complex data analysis with tools, their ability to turn decades of satellite imagery into reliable land-change analysis…
Large language models (LLMs) increasingly support Web-based services that must balance response quality and inference cost across heterogeneous requests.