Knowledge catalogue
We just released the first version of our Creative Writing benchmark, comparing 24 LLMs against human writers across 475 writing prompts. Creative writing is subjective, so the rankings aren't meant t
arXiv:2609.20612v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) lets a language model learn from a frozen copy of itself that sees an answer or a worked solution. Giving the teacher
arXiv:2609.18281v1 Announce Type: new Abstract: The availability and consistency of online services remain vulnerable due to Distributed Denial of Service (DDoS) attacks. These attacks are evolving by
arXiv:2502.12048v4 Announce Type: replace Abstract: Decoding neural activity into human-interpretable representations is a key research direction in brain-computer interfaces (BCIs) and computational
arXiv:2505.07622v2 Announce Type: replace Abstract: Cross-view geo-localization is a promising solution for large-scale localization problems, requiring the sequential execution of retrieval and metri
arXiv:2609.18243v1 Announce Type: cross Abstract: Vision-Language-Action models and World-Action Models have advanced language-conditioned robotic manipulation, yet often leave metric relations among
model : extend Nemotron MTP support (#29018) first fix removed unnecessary declarations Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48188464 macOS/iOS:
model : skip gate_up_exps if TENSOR_SKIP is set (#29014) required for qwen35moe if MTP tensors are fused but not loaded Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/a
arXiv:2609.18366v1 Announce Type: new Abstract: Reliable agent evaluation is complicated by automatic harness optimization, which repeatedly uses a released benchmark B_{rel} to guide a Proposer that
arXiv:2609.18909v1 Announce Type: cross Abstract: Agent benchmarks are substantially more costly to evaluate than conventional LLM benchmarks. Benchmark compression is therefore a natural solution, ye
arXiv:2412.11420v2 Announce Type: replace Abstract: Estimating the 6D pose and 3D size of an object from visual data is a fundamental task in computer vision. Although single-view geometry is a deeply
arXiv:2512.07179v2 Announce Type: replace Abstract: Intelligent Tutoring Systems (ITS) provide personalized learning paths by diagnosing learners' proficiency. Knowledge Tracing (KT) models play a cen
arXiv:2609.18623v1 Announce Type: cross Abstract: State-of-the-art vision-language-action models (VLA) for autonomous driving face critical limitations: excessive parameter counts, inefficient high-re
At Google, we see firsthand how the speed, scale, and sophistication of cyber threats continue to challenge traditional enterprise defenses. Today’s defenders can’t rely on reactive triage or fragment
arXiv:2609.18680v1 Announce Type: new Abstract: Contextual ASR can benefit from semantic cues or from target words explicitly provided in the context. We introduce HearInContext, a Mandarin--English b
arXiv:2609.18908v1 Announce Type: new Abstract: Existing legal benchmarks cover diverse tasks, while continuous monetary remedies remain comparatively underexplored. We introduce ECtHR-NPD, to the bes
arXiv:2609.18431v1 Announce Type: new Abstract: More than 300 million people worldwide are affected by one of over 7,000 known rare diseases, yet diagnosis remains difficult because patients initially
arXiv:2609.17841v1 Announce Type: new Abstract: We develop a hybrid modeling framework for coupling pre-trained numerics-informed neural networks (NINNs) with classical full order models (FOMs) using
arXiv:2609.18317v1 Announce Type: cross Abstract: Large language models (LLMs) suffer from a long-tail deficit: culturally specific facts, particularly those concerning underrepresented regions such a
LLMs lack theories of mind and body, are disembodied, possess neither homeostatic regulating feelings and emotions, are not persistent, and cannot continuously learn or compute. As currently construct
arXiv:2609.19059v1 Announce Type: cross Abstract: Multimodal large language model (MLLM) agents are increasingly used as personal assistants for long-running tasks. Their utility depends on continuity
arXiv:2609.18496v1 Announce Type: cross Abstract: Cybersecurity combines high-stakes analysis with complex technical language, making it an impactful and challenging domain for LLMs. We present MiST (
arXiv:2609.17539v1 Announce Type: new Abstract: We present MudawanSn, a gold-standard resource of 1,271 sentence-aligned pairs manually translated from Wolof into Modern Standard Arabic (MSA). The sou
arXiv:2609.18139v1 Announce Type: new Abstract: Cross-view object geo-localization (CVOGL) locates a target in satellite imagery using drone or street-view queries. Existing methods train separate det
arXiv:2609.17987v1 Announce Type: new Abstract: The traditional Batak Ulos weaving industry faces growing challenges in producing diverse, innovative motifs due to limitations in conventional, manuall
arXiv:2609.17699v1 Announce Type: new Abstract: We present NeMo Data Designer (NDD), an open-source, general-purpose framework for multi-modal synthetic data generation (SDG). Designed to be intuitive
arXiv:2609.19142v1 Announce Type: cross Abstract: World models endow perceptual systems with the ability to predict how scenes evolve under interaction. They are most beneficial when trained on divers
arXiv:2609.18591v1 Announce Type: new Abstract: In-context learning (ICL) enables large language model (LLM) agents to improve decisions using interaction history, yet it remains unclear whether such
Operating large data pipelines requires an orchestration layer that scales smoothly as workloads expand. When your pipelines process millions of complex data points every day to feed predictive models
arXiv:2609.17686v1 Announce Type: cross Abstract: Three recent results describe what look like unrelated LLM reliability problems. Yin et al. (2026) show reasoning RL collapses tool-reliability repres
arXiv:2411.01289v2 Announce Type: replace Abstract: Complex events originate from other primitive events combined according to defined patterns and rules. Instead of using specialists' manual work to
arXiv:2609.16183v1 Announce Type: cross Abstract: Fixed-state recurrences--linear attention and state-space models--are reported to lag behind attention on associative recall, but whole-architecture c
arXiv:2609.16075v1 Announce Type: cross Abstract: Flexible robotic production requires joint decisions on process progression, material routing, resource assignment, temporary cooperation, and simulta
arXiv:2609.17056v1 Announce Type: cross Abstract: Current predictive turn-taking models (PTTMs) achieve strong performance on benchmarks with controlled acoustic conditions and clean audio signals. Th
Anyone interested in trying out a new inference provider? We're testing Gemma 4:26b and Qwen 3.8:27B behind an OpenAI-compatible API and looking for a few users to give them a spin and tell us how it
arXiv:2609.16517v1 Announce Type: cross Abstract: Resume screeners must infer job-relevant competence from resumes whose presentation can vary substantially in wording, structure, stylistic polish, an
arXiv:2609.17464v1 Announce Type: cross Abstract: Multi-agent systems split a task across a tree of agents and justify the split with folklore: smaller contexts, cleaner separation, parallelism. We as
arXiv:2609.16149v1 Announce Type: new Abstract: Despite steady progress in face recognition, current face recognition models still suffer from significant demographic biases. While approaches for bias
arXiv:2609.16011v1 Announce Type: cross Abstract: Embodied conversational agents require synchronized full-body motion (body gestures and facial expressions) that aligns with speech and emotional stat
arXiv:2609.17193v1 Announce Type: new Abstract: Large language model (LLM)-powered agentic AI services increasingly demand low-latency inference, motivating the deployment of LLMs across distributed e
arXiv:2607.27245v2 Announce Type: replace-cross Abstract: Modern policing faces a 'visibility paradox' where law enforcement agencies possess petabytes of Body-Worn Camera (BWC) footage that remains l
arXiv:2609.17384v1 Announce Type: new Abstract: Robot teams that learn a common environment model exchange belief summaries and plan by the expected information gain of their actions. Under conjugate
Google is opening up its smart home to AI agents, letting tools like Claude and Open Claw access and control your connected devices and analyze your home's data using the standardized Model Context Pr
arXiv:2609.16366v1 Announce Type: cross Abstract: When foundation models describe people, recent work in AI fairness, accessibility, and ethics recommends avoiding inferred identity labels (e.g., 'she
arXiv:2609.16964v1 Announce Type: new Abstract: Rapid extraction of structured information from social media is important for humanitarian response, yet existing disaster tweet resources mainly provid
arXiv:2609.17475v1 Announce Type: new Abstract: Capable open-weight models make local coding and reasoning attractive, but their context and execution state strain laptop memory. We present JustFit, a
arXiv:2609.16875v1 Announce Type: new Abstract: Upgrading embedding models typically requires expensive database re-indexing, as new query embeddings are incompatible with existing database embeddings
arXiv:2609.16284v1 Announce Type: cross Abstract: Query-conditioned vision--language models enable fine-grained interpretation by revealing how visual evidence changes with textual queries. However, e
Setup for one long agentic coding session (tools + vision) on a single 5090: Qwen3.8-27B RVN Heretic (ARA abliterated) at Q6_K, 159744 context, 1 slot, q8_0 K/V, DFlash2 speculative decoding, vision p
arXiv:2609.16409v1 Announce Type: new Abstract: Chain-of-thought reasoning has revolutionized natural language processing by enabling large language models (LLMs) to decompose problems into intermedia
arXiv:2609.16900v1 Announce Type: new Abstract: Platform abuse campaigns conceal redirection instructions with emojis, homophones, character decomposition, and redundant symbols, then route users thro
arXiv:2609.16601v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made strong progress on visual question answering and image captioning, yet they still produce fluent clai
arXiv:2609.17414v1 Announce Type: new Abstract: Text-conditioned latent diffusion models perform strongly in video generation and are promising backbones for robotic applications. However, existing ap
arXiv:2609.16871v1 Announce Type: new Abstract: Earth observation is inherently dynamic, yet temporal information in many foundation models is learned through reconstruction, invariance, or retrospect
arXiv:2609.16977v1 Announce Type: new Abstract: Federated learning lets multiple participants train a shared model without pooling raw data, by exchanging locally trained model updates instead. Federa
arXiv:2609.15991v1 Announce Type: new Abstract: Standard subword tokenizers either treat every orthographic variation of a word (such as hello, Hello, HELLO, and Hello) as unrelated vocabulary entries
arXiv:2609.16267v1 Announce Type: cross Abstract: Many operational cases are documented more than once, at different workflow stages and for different purposes, yet model evaluations normally select o
Mistral AI announced on 16 September 2026 that it has partnered with Mozilla to embed privacy, control, and choice features for users interacting with artificial‑intelligence–powered browsing tools. T
TypeSafe AI Inc., a startup founded by a former OpenAI Group PBC researcher who helped develop ChatGPT, emerged yesterday with 40 million in seed funding and a model designed to put artificial intelli
Follow up post of https://www.reddit.com/r/LocalLLaMA/s/nGMyKswrch. Thanks everyone who replied. I didn't change the specs. Might be loosing some of the memory bandwidth but will scale in future if I