Search: “models”

arXiv:2604.22164v1 Announce Type: new Abstract: Recent advances in deep learning have enabled the generation of videos from textual descriptions as well as the prediction of future sequences from inpu

arXiv:2604.22063v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly utilized in clinical reasoning and risk assessment. However, their interpretive reliability in critical

This post discusses a developer's weekend project combining soju and seafood broil with noodles while working on building custom AI agents using Ollama's pi-powered infrastructure and OpenAI models. I

arXiv:2602.07038v2 Announce Type: replace-cross Abstract: Key Information Extraction (KIE) from real-world documents remains challenging due to substantial variations in layout structures, visual qual

arXiv:2604.22142v1 Announce Type: new Abstract: This study examines how large language model rewriting alters the style and narrative texture of personal narratives. It analyzes 300 personal narrative

arXiv:2604.22153v1 Announce Type: cross Abstract: When you ask an AI assistant for advice about your career, your marriage, or a conflict with your family, does it give you the same answer regardless

Hermes Agent tip of the day: There are 4 ways to deal with the model while its running, - Message it, by default, it will interrupt the agent loop, stopping it and making it respond to your new messag

arXiv:2604.20845v1 Announce Type: cross Abstract: Next Point-of-Interest (POI) recommendation plays a crucial role in location-based services by predicting users' future mobility patterns. Existing me

DeepSeek-V4 is a collection of models released by DeepSeek-AI on Hugging Face that represents their latest generation of large language models. The collection likely includes various model sizes and c

This post references a Hugging Face Models page filtered to show quantized versions of the DeepSeek-V4-Flash model, a lightweight variant of DeepSeek's V4 language model. The page displays community-q

arXiv:2604.21027v1 Announce Type: new Abstract: Electronic health record (EHR) question answering is often handled by LLM-based pipelines that are costly to deploy and do not explicitly leverage the h

arXiv:2510.01857v3 Announce Type: replace Abstract: Current approaches to improving reasoning in large language models (LLMs) primarily rely on either supervised fine-tuning (SFT) over expert traces o

LLaDA2.0-Uni is a unified diffusion large language model (dLLM) based on Mixture-of-Experts architecture that seamlessly integrates multimodal understanding and generation. The model supports text-to-

arXiv:2604.21916v1 Announce Type: new Abstract: As frontier language models attain near-ceiling performance on static mathematical benchmarks, existing evaluations are increasingly unable to different

arXiv:2604.21076v1 Announce Type: cross Abstract: Medication reconciliation at clinical handoffs is a high-stakes, error-prone process. Large language models are increasingly proposed to assist with t

arXiv:2604.21210v1 Announce Type: cross Abstract: In continuously monitored quantum systems, the feedback protocol of Garcia-Pintos, Liu, and Gorshkov reshapes the arrow of time: a Hamiltonian H_{meas

arXiv:2604.21255v1 Announce Type: new Abstract: Model distillation is a primary driver behind the rapid progress of LLM agents, yet it often leads to behavioral homogenization. Many emerging agents sh

arXiv:2604.20347v1 Announce Type: cross Abstract: Ultrasound (US)-guided needle insertion is a critical yet challenging procedure due to dynamic imaging conditions and difficulties in needle visualiza

arXiv:2604.19767v1 Announce Type: cross Abstract: We evaluate speculative decoding with EAGLE3 as an inference-time optimization for PayPal's Commerce Agent, powered by a fine-tuned llama3.1-nemotron-

arXiv:2604.20122v1 Announce Type: cross Abstract: We propose a post-hoc adaptive conformal anomaly detection method for monitoring time series that leverages predictions from pre-trained foundation mo

Available on @ollama ! 🤝🤝 Qwen 3.6 27B model is available on Ollama! Use it with all the integrations in Ollama or chat with the model. Chat with the model: ollama run qwen3.6:27b OpenClaw: ollama lau

arXiv:2602.10386v2 Announce Type: replace Abstract: Graph problems are fundamentally challenging for large language models (LLMs). While LLMs excel at processing unstructured text, graph tasks require

arXiv:2604.19790v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed under diverse numerical precision configurations, including standard floating-point formats (e.g.

Imagine every frame of your video, generated live directly from a model. No timeline, no compositor, no render farm. Just exactly what you want to see. Imagine every pixel on your screen, streamed liv

arXiv:2604.20100v1 Announce Type: new Abstract: Robotic autonomy in open-world environments is fundamentally limited by insufficient data diversity and poor cross-embodiment generalization. Existing r

arXiv:2604.07798v3 Announce Type: replace Abstract: Although LLM agents can leverage tools for complex tasks, they still need memory to maintain cross-turn consistency and accumulate reusable informat

This discussion likely covers model selection guidance for users creating storytelling visuals with Stable Diffusion, addressing factors like stylistic output and consistency . The r/StableDiffusion c

arXiv:2504.05336v3 Announce Type: replace-cross Abstract: Integrating quantum computing into deep learning architectures is a promising but poorly understood endeavor: when does a quantum layer actual

Sam Altman praises the inference team's work on efficiently serving a model, suggesting that becoming proficient in AI inference is crucial to the field's progress. The post appears to highlight the t

arXiv:2508.18609v4 Announce Type: replace-cross Abstract: Post-Training Quantization (PTQ) is a critical strategy for efficient Large Language Models (LLMs) deployment. However, existing scaling laws

Deploying large language models (LLMs) in real-world, high-stakes settings is harder than it should be. In high-stakes settings like law, medicine, and cloud incident response, performance and reliabi

arXiv:2604.18724v1 Announce Type: new Abstract: Users typically interact with and evaluate language models via single outputs, but each output is just one sample from a broad distribution of possible

arXiv:2604.19052v1 Announce Type: new Abstract: Understanding a discourse requires tracking entities and the relations that hold between them. While Large Language Models (LLMs) perform well on relati

arXiv:2511.06168v3 Announce Type: replace Abstract: This paper primarily demonstrates a method to quantitatively assess the alignment between multi-step, structured reasoning in large language models

Correction: OpenAI are NOT deprecating that model, the announcement was a mistake Thank you for flagging this, Jeff. This was a mistake: we are not deprecating text-embedding-3-small. We’re looking in

arXiv:2604.19561v1 Announce Type: new Abstract: Large Language Models (LLMs) utilize large amounts of data for their training, some of which may come from copyrighted sources. Membership Inference Att

arXiv:2604.18831v1 Announce Type: new Abstract: Frame-wise semantic segmentation of indoor lidar scans is a fundamental step toward higher-level 3D scene understanding and mapping applications. Howeve

Clem Delangue, CEO of Hugging Face, shared a post about post-training a model using ml-intern, likely referring to a machine learning internship project or internal tool. The post appears to be a casu

arXiv:2604.19578v1 Announce Type: cross Abstract: With the rapid advancement of Large Language Models (LLMs), the academic community has faced unprecedented disruptions, particularly in the realm of a

arXiv:2601.14152v2 Announce Type: replace-cross Abstract: Large language models exhibit surprising sensitivity to the structure of the prompt, but the mechanisms underlying this sensitivity remain poo

arXiv:2604.18658v1 Announce Type: cross Abstract: Existing AI agent safety benchmarks focus on generic criminal harm (cybercrime, harassment, weapon synthesis), leaving a systematic blind spot for a d

arXiv:2604.18919v1 Announce Type: new Abstract: Analyzing topics extracted from text data in relation to external outcomes is important across fields such as computational social science and organizat

arXiv:2604.18946v1 Announce Type: new Abstract: Large reasoning models (LRMs) achieve strong performance on complex reasoning tasks but often generate harmful responses to malicious user queries. This

arXiv:2604.19145v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have become central to autonomous driving systems, yet their deployment is severely bottlenecked by the massive computat

Team is hard at work together with @steipete to make OpenAI models and ecosystem be the obvious way to to enjoy your claw. A lot more to come next week, but a reminder that you can use OpenClaw as par

This is why I won't use proprietary hosted embedding models myself - I am more than happy to pay for a hosted solution (cheaper, faster and more convenient than self-hosting) but I want an open weight