Knowledge catalogue
arXiv:2509.18930v4 Announce Type: replace-cross Abstract: Neural algorithmic reasoning (NAR) is a paradigm that trains neural networks to execute classic algorithms by supervised learning. Despite its
arXiv:2609.13288v1 Announce Type: new Abstract: Video-language models can answer multiple-choice questions with high confidence yet be wrong. We study whether answer-level reliability scores can be im
arXiv:2609.15857v1 Announce Type: new Abstract: This paper establishes a perfect-reconstruction (PR) interpretation of AddUNet and its full-rate realization, and introduces a Residual Full-Rate PR arc
arXiv:2604.03754v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have been shown to encode truth of statements in their activation space along a linear truth direction. Previous
arXiv:2609.14016v1 Announce Type: cross Abstract: TF-IDF and BM25 are two of the most widely used methods for scoring query-document relevance, yet neither has a standard probabilistic derivation that
The Anthropic grift machine! FED BY FEAR THEATER. Take a moment and sit with @kevinnbass chart here. You do not need to be a forensic accountant to understand this money laundering. If this is not pro
arXiv:2609.14245v1 Announce Type: cross Abstract: Context compression reduces generator input in retrieval-augmented generation, but answer quality alone does not characterize citation attribution. We
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The AI industry has taken a doomer turn. What now? AI chiefs D
arXiv:2609.14677v1 Announce Type: new Abstract: Large language models (LLMs) have changed the way people engage with stories. Drawing on public chatbot logs, we can see that when users generate storie
arXiv:2606.21869v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed in multilingual settings, yet the energy costs of serving these models across different
arXiv:2603.15412v2 Announce Type: replace Abstract: The mammalian brain, most extensively studied in rodents and bats, solves an enormous variety of non-spatial cognitive tasks using neural circuitry,
arXiv:2609.15545v1 Announce Type: new Abstract: Hybrid language models can improve capability as well as efficiency, raising the question of how architectural complementarity becomes learned computati
arXiv:2609.15884v1 Announce Type: cross Abstract: We show that logconcave probability measures along the Gaussian cooling path have thin-shell stability, generalizing the thin-shell theorem. This resu
arXiv:2609.13948v1 Announce Type: cross Abstract: A central tenet of human cognition is systematicity, the principle that understanding one concept is inherently tied to understanding close variations
arXiv:2607.17768v2 Announce Type: replace Abstract: Camouflage image generation (CIG) focuses on generating visually concealed objects that seamlessly blend into their backgrounds. Existing methods ty
arXiv:2609.14817v1 Announce Type: new Abstract: In Yoruba, pitch alone separates oko (husband, Mid), okd{o (vehicle, Low), and okd{o (hoe, High) -- the diacritics ARE the tone marks. Yet character err
arXiv:2609.14517v1 Announce Type: cross Abstract: 3GPP has progressively expanded AI/ML lifecycle management in the radio access network, from one-sided model control to Release 20 support for two-sid
arXiv:2609.13547v1 Announce Type: new Abstract: We study switching regret in adversarial multi-armed bandits, where the learner competes with an arm sequence that changes at most S times. When S is kn
arXiv:2609.14970v1 Announce Type: new Abstract: Single-cell foundation models (scFMs) increasingly rely on large-scale transcriptomic pretraining, yet expanding pretraining data can yield diminishing
arXiv:2609.14255v1 Announce Type: cross Abstract: Database management systems increasingly serve dynamic and exploratory workloads, yet many of their decisions still rely on low-level signals such as
arXiv:2411.04319v1 Announce Type: cross Abstract: Text-to-SQL enables users to interact with databases through natural language, simplifying access to structured data. Although highly capable large la
arXiv:2609.15667v1 Announce Type: new Abstract: Agriculture faces many challenges, and robotic systems can play an important role in addressing them by improving the efficiency and sustainability of f
arXiv:2609.13770v1 Announce Type: cross Abstract: Specialist distillation effectively transfers domain expertise to student models via teacher-generated reasoning trajectories. However, when these spe
arXiv:2609.15773v1 Announce Type: cross Abstract: Progress in inclusive household surveys has strengthened socioeconomic evidence for forcibly displaced populations, providing indispensable benchmarks
arXiv:2609.15735v1 Announce Type: cross Abstract: We address the problem of color attribute compression for 3D splats. We show that all images generated by 3D splats are linear in the coefficients for
arXiv:2609.13409v1 Announce Type: cross Abstract: Phase unwrapping is a key step in interferometric and coherent imaging, where the physical quantity of interest is carried by a phase that the instrum
arXiv:2609.13872v1 Announce Type: cross Abstract: As 6G networks transition from theoretical frameworks into operational realities, artificial intelligence (AI) evolves from an add-on optimization too
arXiv:2609.14624v1 Announce Type: new Abstract: Reliable workflow transition detection is important for context-aware surgical assistance and downstream decision support. However, online surgical phas
arXiv:2609.14350v1 Announce Type: new Abstract: Medical vision-language models (VLMs) allow a single model to perform clinical image analysis tasks ranging from diagnosis classification to report gene
arXiv:2609.13728v1 Announce Type: cross Abstract: Historical Linux kernel patches capture defect knowledge that applies beyond their original repair sites. Recent work has shown that large language mo
arXiv:2302.00129v2 Announce Type: replace Abstract: Despite their widespread use, the principles governing the organisation of syntactic dependency trees remain poorly understood. I analyse dependency
arXiv:2603.19502v2 Announce Type: replace-cross Abstract: We study unlabeled MRMP for unit-disk robots in a polygonal environment. Although the problem is hard in general, polynomial-time solutions ex
arXiv:2505.15002v3 Announce Type: replace-cross Abstract: Combinatory Homomorphic Automatic Differentiation (CHAD) was originally formulated as a semantics-driven source-to-source transformation for r
arXiv:2609.13298v1 Announce Type: cross Abstract: Anomaly detection in structured images is challenging in small-data settings where deep learning approaches are costly or impractical. Classical templ
arXiv:2609.14018v1 Announce Type: new Abstract: A correct diagnosis can still be reached for the wrong reasons. In clinical reasoning, every disease hypothesis creates obligations: key evidence must b
arXiv:2609.15680v1 Announce Type: new Abstract: Quadrotor navigation in cluttered 3-D environments requires global guidance while local motion remains subject to collision and motion limits. Harmonic
Two months ago I announced I had found a new dynamic quant method called Voodoo Quant which was SOTA for the most aggressive quant levels on some smaller Qwen3.5 GGUF models. I kept the methodology pr
arXiv:2609.14706v1 Announce Type: cross Abstract: How should a Kronecker-factored Hessian approximation be chosen for post-training quantization? We address this question through WaterKron, which comb
arXiv:2609.15801v1 Announce Type: new Abstract: We introduce loss-conditioned state execution, a model-agnostic method that decides whether to execute a world model's fixed feasible proposal or retain
arXiv:2609.15106v1 Announce Type: new Abstract: Large language models can hallucinate even when the knowledge required for a correct answer is already available. We study this failure through a latent
arXiv:2609.14157v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed with external tools that extend what they can do beyond their own knowledge. Tools help on tasks
arXiv:2609.13676v1 Announce Type: new Abstract: Markov decision processes (MDPs) are used to support decision-making in conservation of biodiversity, but policies, even over small state spaces, can be
arXiv:2609.14184v1 Announce Type: new Abstract: Neural Architecture Search (NAS) automates network design, but evaluating a single candidate requires training it to convergence, making exhaustive sear
arXiv:2609.14790v1 Announce Type: new Abstract: Detecting video highlights, the most informative or engaging moments in a video, is important for applications such as video summarization and content r
arXiv:2609.15048v1 Announce Type: cross Abstract: Let Y_s=sqrt{s}X+Z, where Z is standard Gaussian and independent of the real random variable X. We prove that, under the square-exponential moment con
arXiv:2410.24205v2 Announce Type: replace-cross Abstract: Path planning in complex environments poses significant challenges, particularly in achieving time efficiency while maintaining a fair success
arXiv:2609.12442v1 Announce Type: new Abstract: Automated gait analysis requires accurate classification and interpretable outputs. We propose an integrated framework for classifying healthy gait and
arXiv:2512.14235v2 Announce Type: replace Abstract: Automotive radar has shown promising developments in environment perception due to its cost-effectiveness and robustness in adverse weather conditio
arXiv:2609.12996v1 Announce Type: new Abstract: We prove a full Adam theorem for spectral heavy-tail onset in a closed Gaussian Stein-Hermite teacher-student state-evolution model. The theorem begins
arXiv:2609.12595v1 Announce Type: new Abstract: This paper presents an online coverage path planning algorithm for unknown environments. During navigation, the initially unknown search area is progres
arXiv:2609.12410v1 Announce Type: new Abstract: Dementia is a major and growing global health burden, with Alzheimer's disease (AD) accounting for most cases. Timely and accurate diagnosis is central
arXiv:2609.13100v1 Announce Type: cross Abstract: When providing forecasted probabilities with a predictive model, the ideal model offers perfect calibration: the true probability of the outcome (i.e.
arXiv:2609.12937v1 Announce Type: new Abstract: Robots designed to mediate human groups often fall into the solutionist trap: they are framed as sociable agents that fix problems such as conflict, dis
arXiv:2609.12513v1 Announce Type: cross Abstract: In many settings involving stochastic differential equations, including in diffusion based generative AI, our aim is to accurately generate samples fr
arXiv:2609.11939v1 Announce Type: cross Abstract: Traditional TinyML systems for edge devices achieve high accuracy by relying on fixed-depth models that require a constant number of multiply-accumula
arXiv:2609.12521v1 Announce Type: new Abstract: Unmanned aerial vehicle facade inspection can combine red, green, and blue (RGB) imagery with thermal measurements to screen surface and subsurface anom
arXiv:2410.17355v4 Announce Type: replace Abstract: Due to their capacity to acquire world knowledge from large corpora, pre-trained language models (PLMs) are extensively used in ultra-fine entity ty
arXiv:2609.12278v1 Announce Type: new Abstract: World models let agents plan by predicting the consequences of their actions, but changes in the environment can make them inaccurate. We study the prob
arXiv:2609.12206v1 Announce Type: new Abstract: Bioprinting is emerging as a tissue engineering technique to replace common treatment methods for large scale injuries. While thickness of the BioPrinte
arXiv:2609.12431v1 Announce Type: new Abstract: Automated crack inspection increasingly relies on deep learning, yet its reliability is limited by scarce and weakly controllable defect data. Existing