Knowledge catalogue
Today, we’re thrilled to announce that Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model yet, is now generally available. Designed for ultra-low latency, high-volume tas
In this episode of The Agent Factory, Vlad Kolesnikov and I sat down with Omar Sanseviero from the Developer Experience team at Google DeepMind. We explored the groundbreaking release of Gemma 4: a ne
AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in today’s agentic era require computing infrastructure designed and optimized for these new requirem
arXiv:2604.17494v1 Announce Type: new Abstract: Counterfactual explanations (CFEs) are essential for interpreting black-box models, yet they often become invalid when models are slightly changed. Exis
arXiv:2604.18452v1 Announce Type: cross Abstract: Vision-language modeling is rapidly increasing in popularity with an ever expanding list of available models. In most cases, these vision-language mod
arXiv:2508.15815v3 Announce Type: replace Abstract: Modern large language models (LLMs) are typically trained and deployed using structured role tags (e.g. system, user, assistant, tool) that explicit
arXiv:2604.09952v1 Announce Type: new Abstract: Many applications today use large language models for code generation; however, production systems have strict latency requirements that can be difficul
arXiv:2407.08101v4 Announce Type: replace Abstract: Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, wher
arXiv:2604.08644v1 Announce Type: new Abstract: This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integr
Users on the r/ollama subreddit reported that the **Gemma 4 E4B** model in Ollama offloads layers to RAM even when GPU VRAM is only partially utilized. This behavior is linked to how Ollama and lla...
arXiv:2608.12388v1 Announce Type: cross Abstract: The emergence of orientation selectivity in the primary visual cortex (V1) remains a central question in computational neuroscience. Shirazi's Bayes-M
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:2608.13409v1 Announce Type: new Abstract: Existing predictive models in learning analytics often treat student academic history as a simple sequence, overlooking the concurrent nature of courses
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
I'm working on a local perplexity/AI search comprised of a custom harness and a further trained model. LFM 2.6 is almost to spec with no additional training, it is very good. submitted by /u/thebadsli
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:2608.12446v1 Announce Type: cross Abstract: Sleep stage classification is important for the diagnosis and management of sleep disorders, yet most automatic staging studies evaluate models agains
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:2608.11839v1 Announce Type: new Abstract: Poor air quality in urban areas is driven by a complex chain of processes and presents a significant public health concern. To better understand and con
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:2608.11215v1 Announce Type: new Abstract: Simulating societies of many large language model (LLM) agents is expensive, yet the questions asked of such simulations are usually macroscopic: phase
arXiv:2608.11329v1 Announce Type: cross Abstract: A common approach to adding audio to a vision-language model is to train or adapt a large omni-modal system. We show that a lightweight alternative ca
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
Generative artificial intelligence startup Writer Inc. today announced the release of its next-generation flagship model, Palmyra X6, designed to deliver frontier-level performance for marketing and r
arXiv:2608.10893v1 Announce Type: new Abstract: Certified selective predictors attain whatever coverage they attain; operators impose an automation floor: answer at least a eta-fraction of shifted tar
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:2608.11204v1 Announce Type: cross Abstract: Learning reliable surgical manipulation policies is bottlenecked by the scarcity of action-labeled demonstrations: teleoperated surgical robot (e.g.,
arXiv:2608.09643v1 Announce Type: cross Abstract: AI coding agents now write a growing share of production code, and human security review does not scale at the rate code is generated. The agents in w
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:2608.07693v1 Announce Type: cross Abstract: Generative traffic video forecasting aims to synthesize long-horizon, temporally coherent future videos of traffic scenes from a short observation his
arXiv:2608.08067v1 Announce Type: cross Abstract: Current end-to-end speech dialogue models are primarily optimized for mainstream languages and remain limited in low-resource dialect scenarios due to
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:2608.08244v1 Announce Type: new Abstract: General wearable foundation models are pretrained across broad sensor streams and populations, but are not designed around women's-health tasks. We intr
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:2603.27996v2 Announce Type: replace Abstract: Diffusion models have emerged as a powerful framework for generative tasks in deep learning. They decompose generative modeling into two computation
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
arXiv:2608.07619v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models achieve strong robotic manipulation performance but often degrade under visual and environmental shifts. Latent worl
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:2510.19366v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) scales model capacity through sparse activation, and is becoming an important architecture for large language models (LLMs)
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:2608.08528v1 Announce Type: new Abstract: Enterprise AI coding assistants incur substantial inference spend, and naive token-cost minimization often fails to reduce end-to-end cost once retries,
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
arXiv:2608.08139v1 Announce Type: new Abstract: Establishing the provenance of a language model---including its base checkpoint and possible overlap in training distributions---is a governance challen
arXiv:2608.07762v1 Announce Type: new Abstract: LLM benchmarks can build an organization's reputation and attract customers, but only when results are transparent and verifiable. Unverified claims tha
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