Knowledge catalogue
arXiv:2512.16251v5 Announce Type: replace-cross Abstract: We introduce the Consensus-Bottleneck Asset Pricing Model (CB-APM), which embeds aggregate analyst consensus as a structural bottleneck, treat
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
arXiv:2604.19635v1 Announce Type: cross Abstract: While generative models have set new benchmarks for Target Speaker Extraction (TSE), their inherent reliance on global context precludes deployment in
arXiv:2501.04410v2 Announce Type: replace Abstract: User simulation is an emerging interdisciplinary topic with multiple critical applications in the era of Generative AI. It involves creating an inte
arXiv:2508.00161v3 Announce Type: replace-cross Abstract: The releases of powerful open-weight large language models (LLMs) are often not accompanied by access to their full training data. Existing in
arXiv:2604.18194v1 Announce Type: cross Abstract: Drifting Models [Deng et al., 2026] train a one-step generator by evolving samples under a kernel-based drift field, avoiding ODE integration at infer
arXiv:2604.17709v1 Announce Type: new Abstract: Existing works on large language model (LLM) decomposition mainly focus on improving performance on downstream tasks, but they ignore the poor parallel
arXiv:2604.17286v1 Announce Type: new Abstract: Visual Autoregressive (VAR) modeling inefficiently applies a fixed computational depth to each position when generating high-resolution images. While ex
arXiv:2604.18510v1 Announce Type: cross Abstract: Open-weight language models can be rendered unsafe through several distinct interventions, but the resulting models may differ substantially in capabi
arXiv:2604.17087v1 Announce Type: new Abstract: Recent Multimodal Large Language Models (MLLMs) have demonstrated strong performance on vision-language understanding tasks, yet their inference efficie
arXiv:2604.16377v1 Announce Type: new Abstract: Large Language Models (LLMs) trained on massive code corpora are now increasingly capable of generating code that is hard to distinguish from human-writ
arXiv:2511.01066v3 Announce Type: replace Abstract: We present an ongoing initiative to provide open, very large, high-quality, and richly annotated textual datasets for almost 200 languages. At 30 tr
arXiv:2604.16794v1 Announce Type: new Abstract: Radio astronomy plays a crucial role in understanding the universe, particularly within the realm of non-thermal astrophysics. Images of celestial objec
arXiv:2604.17274v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated exceptional capabilities in various perception and reasoning tasks. Despite this success, ens
arXiv:2604.17053v1 Announce Type: new Abstract: Pluralism alignment with AI has the sophisticated and necessary goal of creating AI that can coexist with and serve morally multifaceted humanity. Resea