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Amanda Silberling / TechCrunch: Twitch says it intends to use videos streamed on its platform to help train Amazon's generative AI models and tells creators how to opt out — The streaming platform Twi

Twitch users can now opt out of allowing their content to be used to train Amazon's generative AI models. Opting out means that 'your streams, VODs, clips, stream chats, and pictures and text on your

arXiv:2608.11114v1 Announce Type: cross Abstract: Probabilistic forecasting plays an essential role in risk-sensitive decision-making, particularly in long-horizon settings. However, existing approach

arXiv:2608.11054v1 Announce Type: new Abstract: Deep learning models have emerged as the standard computational tool for a wide range of applications in genomics. Yet, uncertainty quantification (UQ)

arXiv:2608.10007v1 Announce Type: cross Abstract: The current state-of-the-art (SOTA) deep randomized neural networks, such as deep Random Vector Functional Link (dRVFL) and ensemble deep RVFL (edRVFL

arXiv:2608.10316v1 Announce Type: new Abstract: Multi-modal learning combining medical images and clinical text is promising for disease diagnosis. However, standard multi-modal training leads to shor

arXiv:2608.10835v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) achieve impressive visual reasoning and dialogue capabilities, yet frequently hallucinate content unsupported by th

arXiv:2608.10522v1 Announce Type: cross Abstract: While vision-language models dominate medical representation learning, unstructured text lacks the dense, quantitative diagnostic phenotypes inherent

arXiv:2608.10233v1 Announce Type: cross Abstract: Groundwater variability in Ghana remains poorly characterized due to limited long-term in-situ observations. This study investigates groundwater stora

arXiv:2607.17188v2 Announce Type: replace Abstract: While test-time scaling improves the problem-solving ability of large reasoning models (LRMs) through additional inference-time computation, it can

arXiv:2608.10042v1 Announce Type: cross Abstract: Tool-use LLMs are increasingly asked to act on users' behalf, but existing benchmarks usually focus on profile recall, style imitation, generic tool u

arXiv:2603.18446v2 Announce Type: replace Abstract: Long-context inference remains challenging for large language models due to attention dilution and out-of-distribution degradation. Context selectio

arXiv:2608.11047v1 Announce Type: new Abstract: While existing benchmarks have made substantial progress in evaluating LLMs across STEM domains, financial reasoning over structured data remains compar

What's Changed Models that don't set a repeat_penalty now default to 1.0 (off) instead of 1.1, matching other engines and speeding up speculative decoding; set a per-model parameter if an older model

ModelOpt checkpoints apply a float32 global scale to every projection output on top of the per-group quantization scales. Running the multiply and the cast back to the activation dtype as separate eag

arXiv:2604.07557v2 Announce Type: replace Abstract: Small longitudinal cohorts, common in maternal health, rare diseases, and early-phase trials, limit computational modeling because enrollment is slo

arXiv:2511.19436v2 Announce Type: replace-cross Abstract: Existing Video Detailed Captioning (VDC) methods predominantly rely on costly human annotations or distillation from powerful proprietary mode

arXiv:2608.10665v1 Announce Type: new Abstract: Multimodal large language models often generate reasoning chains containing subtle errors that lead to incorrect answers. Current verification approache

Very interesting new work from Anthropic. (bookmark it) They evolve mind viruses, ideas that spread through a multi-agent system by getting each host to pass them on, then measure what governs the spr

arXiv:2608.10875v1 Announce Type: cross Abstract: Large language model (LLM) agents are increasingly deployed as personal assistants. Existing evaluations, however, mostly use short, self-contained re

arXiv:2608.11201v1 Announce Type: new Abstract: Recent advances in video generation models have significantly improved the realism of synthetic videos, blurring the boundary between generated and auth

arXiv:2608.10903v1 Announce Type: new Abstract: Reliable clinical deployment of machine learning requires models that know when they are likely to fail, particularly for subgroups underrepresented in

arXiv:2608.11174v1 Announce Type: new Abstract: Regulating the latent space to an isotropic Gaussian distribution provides a stable and information-maximized landscape for world model planning. Howeve

arXiv:2608.10408v1 Announce Type: new Abstract: Vision-language models (VLMs) have shown strong capabilities in generating visualization code from textual or visual specifications. However, real-world

arXiv:2607.16173v2 Announce Type: replace Abstract: Open-vocabulary 3D maps let robots answer language queries about what and where, but they assume a static world and cannot answer queries about how

arXiv:2608.10682v1 Announce Type: new Abstract: Single-frame surround-view reconstruction faces severe geometric instability and rendering artifacts due to minimal inter-camera overlap. While existing

arXiv:2608.10359v1 Announce Type: cross Abstract: As information increasingly traverses linguistic boundaries, users require concise cross-lingual representations of long-form content. Nevertheless, l

arXiv:2608.11013v1 Announce Type: new Abstract: Text-only training is a popular paradigm in zero-shot video captioning, where the video distribution is not available to the model during training, lead

arXiv:2505.01656v2 Announce Type: replace Abstract: Analyzing tree morphology, particularly trunk and branch extraction, is valuable for genetic breeding and forestry management. Existing image-based

We are in an insane run of open-weight drops. Every modality, open source is winning. This is what an open source AI summer ☀️ looks like: 🧠 LLMs & Reasoning → DeepSeek-V4-Flash-0731 (my king 👑): 304B

We built a software factory for AI SDK. Each step is an agent, and humans merge changes. Four weeks in: ▪️ The factory authors up to 35% of merged PRs ▪️ It closed 70% of issues in July ▪️ Open bugs a

We have her dash camera which shows they are lying. The agents are wearing body cameras and should have dash cameras of their own. If what they say happened was true they wouldn’t be issuing statement

We wrote a 36-page ArXiv whitepaper on ExtractBench 🧑‍🔬 , our effort to create the most comprehensive, schema-guided, real-world document extraction benchmark. It’s extremely detailed and covers every

arXiv:2307.03587v4 Announce Type: replace Abstract: In non-stationary linear contextual bandits, existing efficient algorithms typically rely on the Weighted Regularized Least-Squares (WRLS) estimator

arXiv:2603.16840v2 Announce Type: replace Abstract: Vision transformers (ViTs) - especially feature foundation models like DINOv2 - learn rich representations useful for many downstream tasks. However

I'm trying to figure out GPU Kernel optimization on older hardware like SM80(ampere) . Is there tools you guys use? Or frameworks? Im waiting for this framework https://www.reddit.com/r/LocalLLaMA/com

arXiv:2608.10986v1 Announce Type: new Abstract: A growing class of methods probes a language model by feeding it its own output: self-consistency, iterated refinement, agentic loops. We ask what such

Warning: Kinda long post. If you don't like reading, please skip for your own sanity. Also, I've got nothing to sell, just a tinkerer, so I just want to share ideas and learn from you guys too. When I

arXiv:2608.10431v1 Announce Type: cross Abstract: Responsible AI (RAI) has become a central concern for technology companies, regulators, and the public. How industry practitioners interpret, implemen

arXiv:2606.16465v2 Announce Type: replace Abstract: AI agents can now take irreversible actions in operational systems, but agent-caused losses are still not clearly assigned, priced, or transferred.

arXiv:2608.09942v1 Announce Type: cross Abstract: It is widely assumed that chain-of-thought (CoT) prompting universally improves LLM reasoning. We investigate this through the conceptual framework of

arXiv:2608.10528v1 Announce Type: cross Abstract: Anchor-based pointwise LLM reranking scores each candidate against a shared reference passage to recover cross-document context at pointwise cost. We

arXiv:2608.10731v1 Announce Type: cross Abstract: Whether an additional general dimension is necessary beyond correlated first-order factors is a property of the population covariance matrix, not of a

arXiv:2608.10084v1 Announce Type: cross Abstract: Public chest X-ray repositories are widely used to train medical AI systems, yet their labels are typically extracted from radiology reports rather th

When should you start post-training your own models? @FireworksAI_HQ CEO @lqiao’s answer: after product-market fit. Not because it's hard... but because only after PMF is the data coming off your prod

arXiv:2608.10489v1 Announce Type: new Abstract: Abundant visual information strengthens vision-language model (VLM) perception, yet massive visual tokens raise inference costs. Existing visual token p