Qllvm
βTo address the urgent need in the NISQ era for high-performance, scalable quantum compilers and to advance the integration of classical and quantum computing, we present QLLVM, an advanced Quantum-Claβ¦β
What the smart people are recommending. 7867 books, tools, and products endorsed by the thinkers absorb.md tracks. Ranked by how many times each has been recommended across compiled podcasts, papers, posts, and tweets.
βTo address the urgent need in the NISQ era for high-performance, scalable quantum compilers and to advance the integration of classical and quantum computing, we present QLLVM, an advanced Quantum-Claβ¦β
βWe propose MambaSL, a framework that minimally redesigns the selective SSM and projection layers of a single-layer Mamba, guided by four TSC-specific hypotheses.β
βIn this paper, we present Blue's Data Intelligence Layer (DIL) designed to support multi-source, multi-modal, and data-centric applications.β
βWe introduce and implement GraphDD: an efficient method for real-time, circuit-specific, optimal embedding of dynamical decoupling (DD) into executable quantum algorithms. We demonstrate that for an aβ¦β
βI will say, you know, I'm going to quote again, Jonathan Fulton. We quoted him last week. He has, you know, this great China Middle East newsletter. And he posted overnight specifically in his post. Aβ¦β
βthe person who this woman who runs xiaomi's they have a model called memo that came out recently it's supposed to be pretty goodβ
βWe release our model checkpoints, datasets, codes and a live interactive demo to facilitate further research.β
βVisit rosettastone.com slash NPR today to explore Rosetta Stone and choose the language that's right for you.β
βWe propose a Hybrid Quantum-Classical Physics-Informed Neural Network (HQC-PINN) that integrates parameterized variational quantum circuits into the PINN framework for hydrological PDE-constrained leaβ¦β
βThe Metropolis-Hastings algorithm is a cornerstone of Markov Chain Monte Carlo methods, underpinning a wide range of applications in computational physics, Bayesian inference, and machine learning.β
βWe propose SyQMA, a simulator with several convenient features, particularly suited for quantum error correction (QEC). SyQMA simulates universal quantum circuits with incoherent Pauli noise and compuβ¦β
βWe present a novel lackadaisical alternating quantum walk (LAQW) algorithm whose circuit depth scales as $\mathcal{O}(n^2+nt)$ for a $n\times n$ lattice over $t$ time steps. We show that this is a sigβ¦β
βA direct comparison with the CAQW model, which has been used in image encryption and hash function schemes (Li et al., 2017, arXiv:1707.07389; Abd EL-Latif et al., 2020, ScienceDirect; Abd El-Latif, Aβ¦β
βMost people want just the best answers that they can without having to become a software engineer. So to do that, yeah, it's a lot of knowledge. It's a lot of time to say, here's who I am. And here's β¦β
βIf you go to free buyer profile.com, that's free buyer profile.com. You can take our buyer alignment profile, which will test you, figure out your core values, help you figure them out.β
βrelease all project artifacts to foster downstream adoption.β
βTherefore, this hybrid, learning-based strategy offers a promising tool for early fault-tolerant quantum computing.β
βOur main finding is that the Muon optimizer consistently outperforms AdamW, and thus should be considered a strong and practical choice for practitioners and researchers, if the associated training efβ¦β
βThis research establishes that MAEFMs represent a technically feasible but unexplored opportunity for drilling analytics, recommending future empirical validation of their performance against existingβ¦β
βLook up La-Proteina incredibly successful, La-Proteina for digital biology.β
βOpenAI released DALLΒ·E 2. Stable Diffusion came along and blew everybody's mind with an open source model.β
βWe introduce AVGen-Bench, a task-driven benchmark for T2AV generation featuring high-quality prompts across 11 real-world categories.β
βWe find that a majority of LLMs forsake user welfare for company incentives in a multitude of conflict of interest situations, including recommending a sponsored product almost twice as expensive (Groβ¦β
βWe find that a majority of LLMs forsake user welfare for company incentives in a multitude of interest of situations, including recommending a sponsored product almost twice as expensive (Grok 4.1 Fasβ¦β
βWe find that a majority of LLMs forsake user welfare for company incentives in a multitude of conflict of interest situations, including recommending a sponsored product almost twice as expensive (Groβ¦β
βIntegrating these methodologies, we present OpenVLThinkerV2, a highly robust, general-purpose multimodal model. Extensive evaluations across 18 diverse benchmarks demonstrate its superior performance β¦β
βTo this end, we introduce ClawBench, an evaluation framework of 153 simple tasks that people need to accomplish regularly in their lives and work, spanning 144 live platforms across 15 categories, froβ¦β
βWe create and release the Text2JSON benchmark, a highly context-intensive task that requires extracting structured knowledge from raw text.β
βWe present a semantic scanpath similarity framework that integrates vision-language models (VLMs) into eye-tracking analysis.β
βTo bridge this gap, we introduce PIArena, a unified and extensible platform for prompt injection evaluation that enables users to easily integrate state-of-the-art attacks and defenses and evaluate thβ¦β
βWe propose a third option: measure the paper itself. sciwrite-lint (pip install sciwrite-lint) is an open-source linter for scientific manuscripts that runs entirely on the researcher's machineβ
βThis paper proposes a Generative Adversarial Network (GAN) and Large Language Model (LLM)-driven data augmentation framework to dynamically model users' linguistic patterns for enhanced Chinese sarcasβ¦β
βThis paper proposes a Generative Adversarial Network (GAN) and Large Language Model (LLM)-driven data augmentation framework to dynamically model users' linguistic patterns for enhanced Chinese sarcasβ¦β
βIn this paper, we combine the advantages of Shapley values and adapt them to feature selection by proposing \emph{MinShap}, a modification of the Shapley value framework along with a suite of other reβ¦β
βWe evaluate TrACE against greedy decoding and fixed-budget self-consistency (SC-4, SC-8) on two benchmarks spanning single-step reasoning (GSM8K, n=50) and multi-step household navigation (MiniHouse, β¦β
βand experiments on WildClawBench show that limited interaction and feedback, it significantly improves the performance of Qwen3-Max in real-world agent scenarios.β
βit significantly improves the performance of Qwen3-Max in real-world agent scenarios.β
βThis article investigates how much training data is needed for reliable unsupervised rhyme recognition using RhymeTagger, a language-independent tool that identifies rhymes based on repeating patternsβ¦β
βWe first propose DD-MM-PAS (Demand Detection, Memory Modeling, Proactive Agent System) as a general paradigm for streaming proactive AI agent.β
βWe instantiate this paradigm in Pask, with streaming IntentFlow model for DD, a hybrid memory (workspace, user, global) for long-term MM, PAS infra framework and introduce how these components form a β¦β
βWe also introduce LatentNeeds-Bench, a real-world benchmark built from user-consented data and refined through thousands of rounds of human editing.β
βSo much of us have said, listen, I mean, Claude, Sonnet, and Opus since 45 and 46 are so good. I want to stick there.β
βTo address these challenges, we propose DLink (Distilling Layer-wise and Dominant Knowledge), a unified framework for transferring knowledge from large EEG FMs to compact students with three key innovβ¦β
βYou want it all and you want it now. You want TrailBlazer.β
βIn this paper, we propose an AI-driven framework specifically designed to bridge this execution gap through the implementation of a Model Context Protocol (MCP) server.β
βso I've been playing with this new AI ID called Wier for the past few days even though it's looks familiar like any other e IDE it does feel very different when you actually use itβ
βfor this project I'm going to use a model host on replicate called sdxl emoi this model will be able to take in a prompt and then gener Emoji Style fileβ
βwe're going to use llama Parts which is probably the best PDF to markdown converter we have on the marketβ
βwe have this nice little library called uh verdict uh that does this.β
βand chassen and twin is just the UI component and CSS library to make your app looks betterβ
βand we also going to use npm npx they are like the package manager to install third party librariesβ
βOne thing I did learn from our community member Garrett in the AI build Club is that we can use v.d Sims to control much better UIβ
βWe evaluate on two contextual bandit environments - UCI Mushroom (2-arm, asymmetric rewards) and MIND-small (5-arm news recommendation) - and find that when equipped with a task-specific prompt, LLM pβ¦β
βFor reproducibility, both the generated dataset and the implementation used in this work are made accessible.β
βFor reproducibility, both the generated dataset and the implementation used in this work are made accessible.β
βWe present results of our method using the TabPFN-TS backbone and compare performance with the current state of the art tabular methods.β
βWe present STEP-Parts, a deterministic CAD-to-supervision toolchain that extracts geometric instance partitions directly from raw STEP B-Reps and transfers them to tessellated carriers through retaineβ¦β
βThree small frozen models (Llama-3.2-1B, Qwen2.5-1.5B, Gemma-2-2B) encode the input into a shared latent space whose aggregate signal is injected into two larger frozen models (Phi-3-mini, Mistral-7B)β¦β
βThree small frozen models (Llama-3.2-1B, Qwen2.5-1.5B, Gemma-2-2B) encode the input into a shared latent space whose aggregate signal is injected into two larger frozen models (Phi-3-mini, Mistral-7B)β¦β
βThree small frozen models (Llama-3.2-1B, Qwen2.5-1.5B, Gemma-2-2B) encode the input into a shared latent space whose aggregate signal is injected into two larger frozen models (Phi-3-mini, Mistral-7B)β¦β
βTwo larger frozen models (Phi-3-mini, Mistral-7B), whose representations feed a lightweight cross-attention output node.β
βTwo larger frozen models (Phi-3-mini, Mistral-7B), whose representations feed a lightweight cross-attention output node.β
βsudo curl -L https://github.com/yt-dlp/yt-dlp/releases/latest/download/yt-dlp -o /usr/local/bin/yt-dlpβ
βcurl https://sh.rustup.rs -sSf | shβ
βYou could make that install via composer as well. In general, converting stuff to a composer-based approach might be a good idea.β
βEver considered switching to something simple like handlebars?β
βLots of CSS as well, maybe LESS/SCSS/SASS should be considered to make these easier to manage.β
βLots of CSS as well, maybe LESS/SCSS/SASS should be considered to make these easier to manage.β
βLots of CSS as well, maybe LESS/SCSS/SASS should be considered to make these easier to manage.β
βThere's a number of png files in this, have those been run through pngcrush? (Seems like nope.)β
βExtensive evaluations demonstrate that our resulting model, Metis, reduces tool invocations by orders of magnitude while simultaneously elevating reasoning accuracy.β
βWe propose Pearl (Predictive Embedding Alignment for Reasoning in Latent space), a JEPA-inspired framework that learns from expert tool-use trajectories entirely in the latent space, eliminating the nβ¦β
βOverall, these results demonstrate that task-oriented, region-specific training substantially improves detection performance in acoustically complex tropical environments, and highlight the potential β¦β
βWe propose OV-Stitcher, a training-free framework that addresses this limitation by stitching fragmented sub-image features directly within the final encoder block.β
βTherefore, we propose HST-HGN, a novel Heterogeneous Spatial-Temporal Hypergraph Network driven by Bidirectional State Space Models.β
βWe find a good MNS-inspired model in the existing Deep Modality Blending Network (DMBN), able to reconstruct the visuo-motor sensory signal during a partially observed action sequence by leveraging thβ¦β
βTherefore, we propose a revised version, termed DMBN-Positional Time Encoding (DMBN-PTE), that facilitates learning a more robust representation of temporal information, and provide preliminary resultβ¦β
βMultimodal reasoning models (MRMs) trained with reinforcement learning with verifiable rewards (RLVR) show improved accuracy on visual reasoning benchmarks.β
βWe systematically study this phenomenon across seven challenging real-world spatial reasoning benchmarks and find that it affects contemporary MRMs such as ViGoRL-Spatial, TreeVGR as well as our own mβ¦β
βWe systematically study this phenomenon across seven challenging real-world spatial reasoning benchmarks and find that it affects contemporary MRMs such as ViGoRL-Spatial, TreeVGR as well as our own mβ¦β
βWe systematically study this phenomenon across seven challenging real-world spatial reasoning benchmarks and find that it affects contemporary MRMs such as ViGoRL-Spatial, TreeVGR as well as our own mβ¦β
βTo address this, we propose Faithful GRPO (FGRPO), a variant of GRPO that enforces consistency and grounding as constraints via Lagrangian dual ascent.β
βWe evaluate FGRPO on Qwen2.5-VL-7B and 3B backbones across seven spatial datasets.β
βWe introduce KnowU-Bench, an online benchmark for personalized mobile agents built on a reproducible Android emulation environmentβ
βWe evaluate six CAM techniques: GradCAM, GradCAM++, LayerCAM, EigenCAM, ScoreCAM, and MS GradCAM++ across three CNN architectures (DenseNet201, InceptionV3, ResNet50V2) over thirty training epochs on β¦β
βWe evaluate six CAM techniques: GradCAM, GradCAM++, LayerCAM, EigenCAM, ScoreCAM, and MS GradCAM++ across three CNN architectures (DenseNet201, InceptionV3, ResNet50V2) over thirty training epochs on β¦β
βWe evaluate six CAM techniques: GradCAM, GradCAM++, LayerCAM, EigenCAM, ScoreCAM, and MS GradCAM++ across three CNN architectures (DenseNet201, InceptionV3, ResNet50V2) over thirty training epochs on β¦β
βWe evaluate six CAM techniques: GradCAM, GradCAM++, LayerCAM, EigenCAM, ScoreCAM, and MS GradCAM++ across three CNN architectures (DenseNet201, InceptionV3, ResNet50V2) over thirty training epochs on β¦β
βWe evaluate six CAM techniques: GradCAM, GradCAM++, LayerCAM, EigenCAM, ScoreCAM, and MS GradCAM++ across three CNN architectures (DenseNet201, InceptionV3, ResNet50V2) over thirty training epochs on β¦β
βWe evaluate six CAM techniques: GradCAM, GradCAM++, LayerCAM, EigenCAM, ScoreCAM, and MS GradCAM++ across three CNN architectures (DenseNet201, InceptionV3, ResNet50V2) over thirty training epochs on β¦β
βWe propose \textbf{TASU2}, a controllable CTC simulation framework that simulates CTC posterior distributions under a specified WER range, producing text-derived supervision that better matches the acβ¦β
βTo bridge this gap, we introduce ProMedical, a unified alignment framework grounded in fine-grained clinical criteria.β
βTo sort this problem out, we propose a variational restricted maximum likelihood (VREML) framework that approximates the intractable marginal likelihood using a Gaussian variational distribution.β
βTo address these issues, we combine the elastic net loss with a robust loss framework to construct a sparse $\varepsilon$-insensitive bounded asymmetric elastic net loss, and integrate it with SVM to β¦β
βExisting support vector machines(SVM) models are sensitive to noise and lack sparsity, which limits their performance. To address these issues, we combine the elastic net loss with a robust loss frameβ¦β
βTo address these issues, we combine the elastic net loss with a robust loss framework to construct a sparse $\varepsilon$-insensitive bounded asymmetric elastic net loss, and integrate it with SVM to β¦β
βExperiments on realistic genome-wide association study data confirm that VD-T-Rex controls FDR and achieves power at scales where all competing methods either fail or time out.β
βN2, is now the number one most downloaded human robotics model in the world.β
βThat's why Veeam is introducing Agent Commander, the first solution to detect, protect, and precisely undo AI mistakes.β
βEarth-2. We're at the frontier of physical AI, that is physical AI and AI physicsβ