Knowledge catalogue
arXiv:2604.25605v2 Announce Type: replace-cross Abstract: Introduction: Semantic search, which retrieves documents based on conceptual similarity rather than keywords, offers advantages for retrieval
arXiv:2410.07719v4 Announce Type: replace Abstract: Despite being widely adopted as a canonical framework for learning robust models, adversarial training suffers from robust overfitting. Existing emp
arXiv:2607.07156v1 Announce Type: new Abstract: Different optimizers have different update biases, but these biases are usually implicit. Existing studies mainly analyze or control such biases from th
Elon Musk announced an upcoming comparison between Grok and Anthropic's Claude Opus with its 1M+ token context window. The post suggests xAI plans to demonstrate how Grok's capabilities compare to Cla
Introducing Muse Spark 1.1 Following Muse Spark in April, here's Muse Spark 1.1 - the first Spark model to offer an API. Meta claim significant improvements in agentic tool calling and computer use. T
arXiv:2607.07027v1 Announce Type: cross Abstract: While generative models enable encoding of complex neuroimaging data for feature generation and reconstruction, developing optimal architectural frame
arXiv:2607.06839v1 Announce Type: cross Abstract: Existing NAS benchmarks (e.g., NAS-Bench, NATS-Bench) cover only narrow, task-specific regions of the architectural design space and lack cross-domain
arXiv:2603.29693v3 Announce Type: replace Abstract: A robust decision-making process must take into account uncertainty, especially when the choice involves inherent risks. Because artificial intellig
Bartosz (@nasqret) is a mathematician who uses GPT-5.6 to solve mathematical problems that were previously considered unsolvable or intractable. This case study from OpenAI highlights how advanced lar
arXiv:2607.06723v1 Announce Type: cross Abstract: Most gradient-based optimization methods move parameters through a fixed background geometry, even when their internal states implicitly define changi
arXiv:2607.07671v1 Announce Type: new Abstract: Probabilistic circuits (PCs) can model complex joint distributions while supporting exact and efficient computation of many inference queries. However,
arXiv:2607.06612v1 Announce Type: cross Abstract: Federated Learning (FL) enables multiple clients to collaboratively train machine learning models while retaining data locality, thereby enhancing use
arXiv:2607.06713v1 Announce Type: cross Abstract: Large language models are rapidly moving towards closing the development cycle, transitioning from simple assistive companions to autonomous contribut
arXiv:2607.07204v1 Announce Type: cross Abstract: Optimization geometrodynamics views optimizer state as evolving geometry. Its full positive-definite quadratic benchmark gives the least affine-invari
arXiv:2607.07646v1 Announce Type: new Abstract: Does RL post-training merely amplify primitive skills already latent in a base model, or can it compose primitive skills into new higher-level strategie
arXiv:2607.07386v1 Announce Type: new Abstract: Linear attention models allow a fixed state size and a fixed amount of compute per token. However, due to their limited state size, linear attention mod
arXiv:2607.07089v1 Announce Type: new Abstract: Relational Deep Learning (RDL) has become a standard methodology for machine learning on relational databases: the database is encoded as a heterogeneou
NVIDIA's NeMo framework addresses the challenge of limited, imbalanced financial NLP data by generating synthetic financial news headlines to fill gaps for trading research, risk modeling, and surveil
arXiv:2506.12885v4 Announce Type: replace Abstract: Crop type classification from optical satellite time series remains limited in its ability to generalize across growing seasons, particularly when c
To be frank, at @QodoAI we were cautious about the last few GPT-5.x upgrades. GPT-5.6 is a clear-cut upgrade. Better code-review quality, fewer tokens, lower latency. @OpenAI cooked here. obviously th
arXiv:2506.19348v2 Announce Type: replace Abstract: Training-free motion customization imposes motion patterns from reference videos onto video generators through test-time computation. Most existing
arXiv:2607.06252v1 Announce Type: cross Abstract: Many problems in science and engineering are difficult to model accurately, either due to unknown physical mechanisms, poorly quantified measurement u
arXiv:2607.06478v1 Announce Type: new Abstract: Traffic signs are crucial components of road safety, serving as visual tools under all lighting conditions. The Manual on Uniform Traffic Control Device
Added Grok 4.5 to the Harbor Town Playable gallery. Here is it's 'build me a procedurally generated 3D simulation showing the evolution of a harbor town from 3000 BCE to 3000 AD, it should look beauti
arXiv:2607.06291v1 Announce Type: new Abstract: Game worlds have traditionally been built through labor-intensive production pipelines, making them costly to develop, difficult to customization, and e
arXiv:2607.06445v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly utilized as the conditioning backbone for diffusion-based image editing due to their remarkable multimo
arXiv:2607.06222v1 Announce Type: new Abstract: Extreme subsea environments often cause severe feature de-gradation and estimator divergence in underwater visual-inertial SLAM. Although sensors like D
arXiv:2607.05898v1 Announce Type: new Abstract: Evaluating whether unlearning algorithms truly remove training data influence remains an open challenge. We propose a practical auditor that computes da
arXiv:2607.06364v1 Announce Type: new Abstract: Mapping cloud security controls to technical metrics is currently a manual process. This paper proposes domain adaptation of Sentence Transformer models
arXiv:2601.06521v2 Announce Type: replace-cross Abstract: While humans develop core visual skills long before acquiring language, contemporary Multimodal LLMs (MLLMs) still rely heavily on linguistic
arXiv:2607.05694v1 Announce Type: cross Abstract: Logit-based watermarking is a widely used mechanism for identifying LLM generated content, yet its effectiveness is governed by a fundamental trade-of
arXiv:2607.06522v1 Announce Type: new Abstract: Vision-language models (VLMs) struggle to generalize in interactive physical reasoning, particularly under unseen tasks and environments. Two key failur
arXiv:2607.04135v1 Announce Type: cross Abstract: The remarkable ability of modern neural networks to generalize improves with increasing network capacity, even when the number of model parameters or
Busy couple days ahead! Today, @nvidia Nemotron 3 Ultra support for @LangChain Deep Agents at a fraction of the cost -w/ Quick Start Prompt Tomorrow is Wikimania🔥 @hwchase17 is chatting with with @Bra
Cognition: Cognition releases SWE-1.7, trained from Kimi K2.7 and available at 1,000 tokens/second, claiming it nears GPT-5.5 and Opus 4.8 on benchmarks at a lower cost — Today, we're launching SWE-1.
arXiv:2607.05790v1 Announce Type: new Abstract: Tool-augmented large language models extend their capabilities beyond parametric knowledge through external tools, but tend to invoke them unnecessarily
arXiv:2505.10356v3 Announce Type: replace Abstract: Decoding language from the human brain remains a grand challenge for Brain-Computer Interfaces (BCIs). Current approaches typically rely on unimodal
arXiv:2607.05866v1 Announce Type: cross Abstract: Under a fixed privacy budget, the utility of differentially private (DP) training is ultimately determined by its optimization efficiency. Standard fi
arXiv:2607.06326v1 Announce Type: new Abstract: Large language models deployed in open-world applications require safety guardrails that are both robust to complex risks and efficient enough for low-l
arXiv:2607.06165v1 Announce Type: new Abstract: Omni-directional (360{eg}) cameras provide embodied agents with a holistic view of their surroundings, making them suited for directional reasoning in t
arXiv:2607.06565v1 Announce Type: cross Abstract: Unified 3D foundation models aspire to generate 3D assets and reason about them in language within a single backbone, but their text-3D interaction re
arXiv:2607.05457v1 Announce Type: cross Abstract: Deep neural networks often contain substantial hidden-state redundancy, but most compression methods operate directly on weights, neurons, or quantise
arXiv:2607.06230v1 Announce Type: cross Abstract: Parameterized quantum circuits (PQCs) are increasingly used as policies and value functions in quantum reinforcement learning, yet it remains unclear
arXiv:2607.06125v1 Announce Type: cross Abstract: Neural decompilation is increasingly studied as a code-generation problem, yet its evaluation methodology remains underdeveloped for modern languages.
Finally can share that I have been testing GPT-5.6 early and oooo boy. It is an execution beast. So much so that I think 5.6 is the absolute wrong name considering how big of a leap this felt to me. T
arXiv:2607.05682v1 Announce Type: new Abstract: LLM systems for scientific discovery increasingly assist with ideation, literature synthesis, experiment planning, and report generation, but the first
arXiv:2308.16041v2 Announce Type: replace Abstract: Talking head generation has progressed rapidly from landmark- and GAN-based facial animation to diffusion models, neural rendering, 3D-aware avatars
arXiv:2607.05906v1 Announce Type: new Abstract: 3D Gaussian Splatting provides an explicit representation that jointly models geometry and appearance, serving as a scalable foundation for 3D represent
arXiv:2607.05493v1 Announce Type: new Abstract: Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to
arXiv:2607.05956v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into scientific research workflows, particularly for bibliographic discovery and literature synthesis, r
arXiv:2607.05814v1 Announce Type: cross Abstract: Real-time decoding is a major bottleneck in scaling quantum error correction (QEC) from noisy intermediate-scale quantum (NISQ) devices to fault-toler
arXiv:2603.06924v2 Announce Type: replace Abstract: In classical Informative Path Planning (C-IPP), robots are typically modeled as mobile sensors that acquire digital measurements such as images or r
Local AI just got faster. ⚡️ We worked with @ggerganov to add DFlash support in llama.cpp delivering ~2x faster inference. llama.cpp recently added DFlash support to its speculative decoding arsenal.
arXiv:2607.05690v1 Announce Type: new Abstract: Language agents run a loop - observe, reason, act - but the memory they reason over sits outside it: a store queried at most once per turn. We study the
arXiv:2607.05736v1 Announce Type: new Abstract: Molecular property prediction often relies on isolated data modalities, where continuous 3D graph neural networks (GNNs) struggle to efficiently capture
arXiv:2607.05623v1 Announce Type: new Abstract: We re-implement the NAVER LABS IWSLT 2025 instruction-following pipeline for the IWSLT 2026 Shared Task (constrained condition, short audio track), adap
arXiv:2607.05955v1 Announce Type: cross Abstract: Interactive 3D segmentation aims to extract object masks in point clouds with minimal user clicks. Despite recent progress, most existing approaches s
arXiv:2607.05805v1 Announce Type: new Abstract: Dilution refrigerators are the enabling infrastructure of superconducting quantum computers, yet their fault diagnosis is still dominated by threshold a
Own the frontier: 'In our evals, Nemotron 3 Ultra with a tuned LangChain Deep Agents harness provides advanced agent performance at a much lower inference cost. The main takeaway is that agent perform
arXiv:2607.05605v1 Announce Type: new Abstract: With the rapid advancement of image generation technologies, perceptual quality assessment of AI-generated images has emerged as a crucial research dire