Knowledge catalogue
arXiv:2608.18597v1 Announce Type: new Abstract: Protein language models are widely used priors for protein sequence design, and a growing body of work controls them at inference time as an alternative
🐦Ornith 1.5 series models are now available on ollama! 🫡Thanks to our awesome friends at @ollama 👀Come give Ornith 1.5 a try! https://ollama.com/library/ornith-1.5 Aloha! 🌺Introducing Ornith-1.5, a fa
arXiv:2608.18628v1 Announce Type: cross Abstract: Aligned vision-language models (VLMs) are designed to balance grounded visual reasoning with safe generation behavior. However, we observe a striking
How Anthropic's new results post would read without the PR: Claude orchestrated open-source protein design models, PXDesign, RFdiffusion, Genie, BoltzGen, from a 30k-token expert prompt and 12,500 H10
arXiv:2607.16207v2 Announce Type: replace Abstract: Public open-weight language models are often fine-tuned on private or domain-specific data before deployment, creating a need to audit whether indiv
arXiv:2608.17973v1 Announce Type: new Abstract: Diffusion models have achieved remarkable success in image and video generation, yet the high computational cost of iterative sampling remains a critica
arXiv:2608.17328v1 Announce Type: new Abstract: Facial biometric recognition systems currently face compound threats intertwining generative AI and high-fidelity physical spoofing. Existing defenses s
arXiv:2608.15979v1 Announce Type: new Abstract: Large language models produce outputs presented as discoveries - new proofs, conjectures, or molecules. Whether such an output that appears creative is
arXiv:2608.16887v1 Announce Type: new Abstract: This paper investigates an increasingly important topic in generative modeling: pixel-space diffusion models. Although numerous studies have explored th
As models become more capable, the risks associated with developing and testing them internally also grow. We temporarily paused reinforcement learning (RL) training on our latest models intended for
arXiv:2501.06286v2 Announce Type: replace-cross Abstract: Multi-hop question answering requires a system to identify and integrate evidence distributed across documents, yet large language models rema
arXiv:2608.16594v1 Announce Type: new Abstract: Cancer survival prediction supports treatment planning, risk stratification, and follow-up management. Existing methods use structured clinical variable
arXiv:2608.16210v1 Announce Type: new Abstract: Aggregate accuracy hides where models succeed and fail. Estimating conditional performance profiles from gold labels alone is expensive, while cheap aux
arXiv:2502.11603v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit strong natural language understanding capabilities but also inherit and amplify societal biases, particul
arXiv:2608.15107v1 Announce Type: new Abstract: Federated learning (FL) is a practical framework that can train models on distributed user data while guaranteeing data privacy; however, due to heterog
Yesterday I downloaded Qwen3.8 as MLX from the Ollama library from the commandline on a MAC. Simple 'Ollama Pull xxx' This is the answer I get when I ask it what model it is... I swear to god this is
arXiv:2608.15535v1 Announce Type: new Abstract: We present L3Cube-IndicQuest v2, a large-scale gold-standard multilingual question-answering benchmark for evaluating the India-specific factual knowled
arXiv:2608.15156v1 Announce Type: cross Abstract: World models may predict the future without making clear which parts of their hidden state actually drive those predictions. We ask whether a small, d
arXiv:2606.19888v2 Announce Type: replace-cross Abstract: Modeling long-sequence medical time series data, such as electrocardiograms (ECG), poses significant challenges due to high sampling rates, mu
arXiv:2509.21576v2 Announce Type: replace Abstract: The advancement of vision language models (VLMs) has empowered embodied agents to accomplish simple multimodal planning tasks, but not long-horizon
arXiv:2608.14604v1 Announce Type: cross Abstract: Small language models in the ten to one hundred million parameter range are attractive for on device inference, rapid experimentation, and controlled
arXiv:2602.09992v2 Announce Type: replace-cross Abstract: Several recent contributions have evaluated the Poverty of the Stimulus Hypothesis (PoSH) using Artificial Neural Networks (ANNs). The results
Hello all, I'm fairly new to the whole Llm space and could really use some guidance from people who've done similar work. Im building a pipeline to extract structured data from large-batch of invoices
So many comments begging for these models, and I get it. People from the labs frequent r/LocalLLaMA, so maybe the begging comments aren't useless. They make demand known at least. Same with polls, etc
arXiv:2608.12342v1 Announce Type: new Abstract: Ensuring the accuracy of financial documents is critical for economic analysis, regulatory compliance, and corporate decision-making. Several studies ha
arXiv:2608.12374v1 Announce Type: cross Abstract: Language models (LMs) struggle with logical tasks like reasoning on syllogisms. It has been shown that Knowledge Representation (KR) plays a crucial r
arXiv:2608.13069v1 Announce Type: new Abstract: Large language models (LLMs) are predominantly aligned to function as passive, sycophantic assistants. We challenge this default paradigm by empirically
arXiv:2608.13395v1 Announce Type: new Abstract: Reinforcement learning improves autonomous-driving vision-language-action (VLA) models by evaluating trajectories sampled from the current policy. Group
arXiv:2608.12343v1 Announce Type: new Abstract: AI chatbots are widely used by students as knowledge sources, yet LLM benchmarks rarely assess interpretative historical reasoning. We evaluate eight le
Good day to all. I'm fairly new running local models and would like to pick your brains on an issue I'm running into. I'll first tell you the issue, then give you my set up. I run into issues where th
arXiv:2608.12630v1 Announce Type: cross Abstract: While large language models can generate entire novels, there is little information about the level of formal variation in their output over many gene
arXiv:2608.12564v1 Announce Type: new Abstract: Automating empirical research is a long-standing direction of AI. Recent automatic research (AutoResearch) agents bring this goal within reach, as moder
arXiv:2608.11810v1 Announce Type: new Abstract: Air traffic controllers perceive traffic complexity through the radar display, suggesting that a computer vision model operating on the same imagery may
arXiv:2608.11534v1 Announce Type: new Abstract: In medical imaging, the clinical value of Computed Tomography (CT) lies not only in depicting current disease status, but crucially in enabling longitud
arXiv:2603.00056v2 Announce Type: replace-cross Abstract: STEM Mental models can play a critical role in assessing students' conceptual understanding of a topic. They not only offer insights into what
arXiv:2608.11797v1 Announce Type: new Abstract: Model merging by task arithmetic works until it doesn't, and the field diagnoses why with magnitudes: layerwise representation bias, deviations from cro
arXiv:2608.11657v1 Announce Type: cross Abstract: We introduce Semantic Lenia, an artificial life framework that transforms Large Language Model (LLM) inference from a static optimization problem into
arXiv:2608.10393v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong capabilities in controlling robots across diverse manipulation tasks. However, their adversarial r
arXiv:2512.05746v3 Announce Type: replace Abstract: Diffusion models have demonstrated significant applications in the field of image generation. However, their high computational and memory costs pos
arXiv:2608.10273v1 Announce Type: cross Abstract: Deploying large language models (LLMs) for decision support in emergency departments (EDs) faces two major challenges: privacy risks of transmitting p
Palo Alto Networks Inc. said today its Unit 42 consulting arm will put OpenAI Group PBC’s frontier cyber models to work inside customer environments, expanding a service it launched earlier this year
arXiv:2608.10004v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) provide an interpretable framework by grounding predictions in human-understandable concepts, enabling semantic inspect
arXiv:2608.07651v1 Announce Type: new Abstract: Large language models (LLMs) show promise in medical image interpretation but suffer from hallucination, limited accuracy, and run-to-run inconsistency.
arXiv:2508.16085v2 Announce Type: replace Abstract: Histopathology is essential for cancer diagnosis and treatment selection, and pathology foundation models learn visual representations from whole-sl
arXiv:2608.08736v1 Announce Type: new Abstract: Fitness Action Quality Assessment (AQA) is important for intelligent sports training, yet the capabilities of Multimodal Large Language Models (MLLMs) i
arXiv:2608.09893v1 Announce Type: cross Abstract: Thinking Mode Fusion (TMF) enables large language models to support both concise responses and long-form reasoning by unifying a non-thinking mode and
Needs a lot of requests compared to Qwen (almost twice) and Gemma (almost x3). Final score is fine, even though it is 'not a coding model' https://wonderrico.github.io/local_llm_benchmark/benchmark-ma
☁️Mistral is bringing together the inference infrastructure, open models, and long-term commitments Europe needs to control its AI future, and setting a roadmap for the world. 🧵: https://mistral.ai/ne
arXiv:2603.28590v3 Announce Type: replace Abstract: Large language models (LLMs) can generate chains of thought (CoTs) that are not always causally responsible for their final outputs. When such a mis
arXiv:2608.09227v1 Announce Type: new Abstract: Omnimodal language models (OLMs) enable unified audio-visual understanding, but processing long joint token sequences makes inference computationally pr
arXiv:2608.09772v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) have demonstrated strong performance on multimodal benchmarks, yet it remains unclear whether they genuinely reason
arXiv:2608.08081v1 Announce Type: cross Abstract: Large mixture-of-experts (MoE) language models with 26--120 billion parameters exceed the memory capacity of consumer devices through three simultaneo
arXiv:2606.22790v2 Announce Type: replace-cross Abstract: In this paper, we investigate the tradeoffs between compute allocation and model performance for two speech processing tasks: Automatic Speech
arXiv:2608.08650v1 Announce Type: new Abstract: Mixture-of-Experts models increase parameter capacity while keeping the computation activated by each token bounded, but their architectural evolution c
Hi all, I'm seeing so many conversations from people discussing how they're 'using the models wrong' and 'don't use Sol max as high is enough for you', yet all the conversations lack the nuance of wha
arXiv:2608.07510v1 Announce Type: cross Abstract: Increasingly, AI video models are marketed as 'world simulators,' suggesting their ability to model infinite realities. Despite such claims, these mod
arXiv:2608.08060v1 Announce Type: new Abstract: Fine-tuning vision-language models such as CLIP typically requires backpropagation (BP) through the full model, which is infeasible when only forward-pa
arXiv:2608.07427v1 Announce Type: new Abstract: LLM inference accounts for over 90% of AI operational energy, scaling directly with input token count---a critical inefficiency for telecom network anal
arXiv:2608.06613v1 Announce Type: cross Abstract: Self-supervised 3D medical foundation models are increasingly used as general-purpose feature extractors, yet their sensitivity to MRI artifacts remai
arXiv:2608.07199v1 Announce Type: new Abstract: Optimizing 3D shapes within the latent spaces of deep generative models is fundamental to computer assisted engineering, yet remains prone to a critical