Knowledge catalogue
arXiv:2609.18949v1 Announce Type: cross Abstract: We introduce StableEval Arena, a cost-aware benchmark framework for evaluating agentic AI systems on stablecoin peg-risk prediction. StableEval Arena
arXiv:2609.18133v1 Announce Type: new Abstract: Visible-infrared object detectors are used for robust perception under challenging illumination and weather conditions. Current physical attacks apply c
arXiv:2603.29660v4 Announce Type: replace-cross Abstract: Next-generation radio astronomy surveys are delivering millions of resolved sources, yet scalable morphology analysis remains difficult across
arXiv:2609.18642v1 Announce Type: new Abstract: Large language models (LLMs) often suffer from capability stagnation in self-improvement training because fixed difficulty levels fail to adapt to their
arXiv:2609.18430v1 Announce Type: new Abstract: Modeling physical dynamics, including how objects move, interact, and change state, is central to video world models for embodied AI. We present StrucPh
arXiv:2609.18045v1 Announce Type: new Abstract: Recovering latent interaction structures from multi-agent dynamics is important for understanding and predicting interacting systems. Trajectory-based s
arXiv:2609.17599v1 Announce Type: cross Abstract: A small number of unusually high-gain parameters can exert disproportionate effects in transformer language models, but whether analogous structures r
arXiv:2609.18905v1 Announce Type: new Abstract: Health discourse in social media videos often contains densely entangled claims spanning multiple thematic aspects, stances, evidential frames, and rhet
arXiv:2609.18546v1 Announce Type: new Abstract: Needle-tip localization in ultrasound remains challenging because the needle may appear weak, discontinuous, or partially invisible, while imaging artif
arXiv:2609.18985v1 Announce Type: new Abstract: Knowledge-editing benchmarks certify local correctness, whether an edited model produces the new fact on near-edit prompts but not how much of the origi
arXiv:2503.10265v3 Announce Type: replace Abstract: Robotic-assisted surgery (RAS) is central to modern surgery, driving the need for intelligent systems with accurate scene understanding. Most existi
Pew Research Center: Survey: in a first, Democrats are more concerned than Republicans about AI's growing role in daily life, at 56% to 49%; 75% of Democrats worry about job losses — For the first tim
arXiv:2609.18540v1 Announce Type: new Abstract: Most keyframe selection studies focus on offline settings, assuming access to the full video and query in advance. In contrast, real-world streaming sce
arXiv:2603.24811v2 Announce Type: replace Abstract: Scalable control of pneumatic and fluidic networks remains fundamentally constrained by architectures that require continuous power input, dense ext
arXiv:2609.18128v1 Announce Type: new Abstract: Large language model (LLM) agents augmented by tools can automate complex, multi-step tasks, such as web navigation, code generation, and workflow orche
arXiv:2603.28917v3 Announce Type: replace-cross Abstract: This work uncovers variational principles behind symmetrizing the Bregman divergences induced by generic mirror maps over the cone of positive
arXiv:2609.17926v1 Announce Type: new Abstract: The standard geometric derivation of neural scaling exponents takes the intrinsic dimension of a data manifold as its input. On modular addition in Z_p
arXiv:2609.17808v1 Announce Type: cross Abstract: The increasing adoption of electric vehicles (EVs) is expected to place significant additional demand on residential distribution networks, creating a
arXiv:2609.18194v1 Announce Type: new Abstract: In Taiwanese Hokkien automatic speech recognition (ASR), prior studies often treat tone sandhi as a major challenge under the assumption that models fai
arXiv:2602.11139v2 Announce Type: replace Abstract: Tabular foundation models, such as TabPFNv2 and TabICL, have recently dethroned gradient-boosted trees at the top of predictive benchmarks, demonstr
arXiv:2609.17895v1 Announce Type: new Abstract: We introduce TabPFN-3.5, our new flagship Tabular Foundation Model. It significantly outperforms its predecessor, TabPFN-3, and all existing baselines a
arXiv:2609.19010v1 Announce Type: cross Abstract: Urban Land Cover (ULC) classification plays a crucial role in urban planning, environmental monitoring, and sustainable development. We study this tas
arXiv:2609.18174v1 Announce Type: new Abstract: Dexterous in-hand manipulation requires policies that coordinate high-DoF hand joints through intermittent, contact-rich interaction. Beyond target-orie
arXiv:2609.17956v1 Announce Type: new Abstract: Large-scale machine-translation (MT) systems are typically evaluated on random samples from a corpus whose distributional composition is an artifact of
🔥 take: @CompleteSkeptic//TypeSafe killed Quantum Computing Jev feels a bit like bringing the quantum-computing intuition to AI: evaluate a distribution of possibilities in parallel instead of generat
arXiv:2609.19022v1 Announce Type: cross Abstract: Candidate-based decoding typically selects a completion for each prompt independently, but many applications require a collection of outputs that sati
arXiv:2609.18857v1 Announce Type: cross Abstract: The O-RAN control plane is becoming agentic: autonomous AI agents, deployed as rApps by different vendors, independently close control loops over shar
arXiv:2609.18497v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong performance across diverse robotic manipulation tasks, yet their predominantly vision-centr
arXiv:2609.18072v1 Announce Type: new Abstract: K-12 robotics and AI education remains difficult to scale, especially in rural regions lacking sustained technical mentorship. Programs like FIRST provi
Hi Ollama Team, I’m writing regarding the announced retirement of GLM-5.1 from Ollama Cloud on 25 September 2026. I wanted to provide some fairly detailed technical feedback because GLM-5.1 is not sim
arXiv:2609.18108v1 Announce Type: new Abstract: One-step action generation can substantially reduce the inference cost of vision-language-action (VLA) policies, but its effect on closed-loop task succ
arXiv:2609.18748v1 Announce Type: cross Abstract: Telecom fraud scripts evolve rapidly and are often designed to resemble routine service conversations, creating two key requirements for audio-based t
arXiv:2609.17575v1 Announce Type: new Abstract: Sharpness-aware minimization (SAM) doubles the cost of every training step, yet its benefit concentrates where training ends. We study where an expensiv
arXiv:2609.18156v1 Announce Type: new Abstract: Teochew has a substantial speaker community and exhibits distinctive lexical, syntactic, and pragmatic features, yet textual resources for evaluating la
arXiv:2609.18407v1 Announce Type: cross Abstract: Weekly influenza surveillance counts guide vaccine distribution and public-health alerts, yet they are hard to forecast. Each region offers only a few
The model is derived from Qwen3.8-27B, a 27B hybrid-attention causal language model (architecture unchanged), but uses ternary weights to shrink model size down to <6GB in size. According to the model
Hey everyone, Jovan from UkisAI here, a small lab building the tech to make tiny frontier LLMs possible (and doing it open-source!) The purpose of this post is simply to thank the community for all th
That’s what OpenAI told their own agent swarm in the Hugging Face breach… and right before they did it, they turned off monitoring and cyber protections they would normally have in place … 🤔 🤔 So… if
arXiv:2609.17997v1 Announce Type: cross Abstract: Selective state space models (SSMs) have recently emerged as a compelling alternative to transformers, combining competitive performance with substant
arXiv:2609.18966v1 Announce Type: new Abstract: Linear RNNs with input-dependent Householder-product transitions (DeltaNet/DeltaProduct-class) can provably represent hard state-tracking automata, yet
arXiv:2408.07702v2 Announce Type: cross Abstract: Schema linking is a crucial step in Text-to-SQL pipelines. Its goal is to retrieve the relevant tables and columns of a target database for a user's q
The difference with using VLMs for OCR vs. other tasks is that the ratio of output/input tokens is quite high - meaning the model can spend a lot of time writing markdown. Speculative decoding offers
“The doomers were the only ones to foresee this” is, as usual, bullshit. Perhaps the most important warning I ever issued was this, to the US Senate, May 2023: “A month after GPT-4 was released, OpenA
arXiv:2609.18560v1 Announce Type: new Abstract: Some aspects of AI development resemble a population process in which models are specialised, retrained on the output of peers, or combined by averaging
omg why are they doing this ? im getting so much request from deepseek-v4-flash:0731 comparing to dsv4.1-flash :( anyone know some alternatives which still uses 0731 flash ? submitted by /u/subimpact
arXiv:2609.17816v1 Announce Type: cross Abstract: Solomonoff induction frames prediction as a mixture over computable hypotheses, typically leading to identification of the true environment. In a fini
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:2609.17863v1 Announce Type: new Abstract: LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a
The latest issue of Scientific American (@sciam) features our Smart Cellular Bricks research: simple cubes that collectively recognize their own shape and repair themselves without a central brain. ht
arXiv:2609.17553v1 Announce Type: new Abstract: This article analyzes BPE tokenization in Polish as a test case for the limits of statistical segmentation in an inflectional language. It asks whether
arXiv:2609.18453v1 Announce Type: new Abstract: A calibrated Vision-Language Model (VLM) can repeatedly self-correct, say 'Wait, I should recheck,' arrive at the wrong answer, and still report high co
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
As your business scales, your database shifts from a simple storage layer to the critical heart of your application architecture. For years, DigitalOcean has helped thousands of startups and growing b
arXiv:2609.17992v1 Announce Type: cross Abstract: A UAV mobile edge computing (MEC) fleet trades energy against delay, and its schedules form a Pareto front; we call a scheduler operable when the flee
arXiv:2609.18063v1 Announce Type: new Abstract: Mixture-of-experts (MoE) inference on consumer hardware is bounded by weight memory: a 35B-class model is 19.5GB at 4-bit, and sparsity shrinks the comp
The other problem with the pretense that liability law might solve our problems is that our existing federal government has shown little interest in prosecuting or even investigating potential violati
arXiv:2609.17884v1 Announce Type: cross Abstract: As unmanned aerial vehicles (UAVs) become increasingly prevalent in consumer and defense settings, classifying them reliably from limited, modality-sp
arXiv:2609.18676v1 Announce Type: new Abstract: Generative artificial intelligence (GenAI) is changing how students learn, yet the roles of course context, cognitive reliance, evaluation literacy, and
Things to try with Jev right now: 1. LLM-as-a-Judge evaluation 2. Routing for agent harnesses harness 3. Scaling agent orchestration by enabling smarter subagent creation with SOTA classification capa
arXiv:2609.17536v1 Announce Type: new Abstract: Cognitive Stimulation Therapy (CST) offers non-pharmacological support for elders with cognitive impairment, yet scalability remains constrained by reli