Knowledge catalogue
arXiv:2510.13394v4 Announce Type: replace Abstract: Spatial reasoning ability is crucial for Vision Language Models (VLMs) to support real-world applications in diverse domains including robotics, aug
arXiv:2602.24043v2 Announce Type: replace Abstract: Reconstructing 3D clothed humans from monocular images and videos is a fundamental problem with applications in virtual try-on, avatar creation, and
arXiv:2608.23879v1 Announce Type: cross Abstract: Cardiac cine-MRI serves as a direct visual indicator of cardiovascular hemodynamics by capturing the continuous wall motion of the aorta. Quantifying
arXiv:2608.24870v1 Announce Type: new Abstract: Group-relative reinforcement learning waits for sibling rollouts of the same prompt, which is costly for long and variable tool-use trajectories. Single
arXiv:2603.00188v2 Announce Type: replace-cross Abstract: Training-free KV cache compression is essential for deploying vision-language GUI agents under memory and latency constraints, yet existing me
arXiv:2509.03754v2 Announce Type: replace-cross Abstract: Responding to rising global food security needs, precision agriculture and deep learning-based plant disease diagnosis have become crucial. Ye
arXiv:2505.01361v3 Announce Type: replace Abstract: Temporal difference (TD) learning is a foundational algorithm in reinforcement learning (RL). For nearly forty years, TD learning has served as a wo
arXiv:2503.16855v3 Announce Type: replace Abstract: Hand gesture-based Sign Language Recognition (SLR) serves as a crucial communication bridge between deaf and non-deaf individuals. While Graph Convo
arXiv:2608.23952v1 Announce Type: cross Abstract: Federated video anomaly detection trains model collaboratively without sharing raw surveillance footage, but limited server-side visibility lets compr
arXiv:2608.24804v1 Announce Type: new Abstract: We present StarHarness, a framework for evolving environment-specific agent harnesses while keeping model weights fixed. The evolved harness can include
arXiv:2608.23601v1 Announce Type: cross Abstract: EDA flow parameter tuning is critical for quality-of-results~(QoR), yet the parameter space is large, tightly coupled, and full evaluations are prohib
arXiv:2608.24136v1 Announce Type: new Abstract: Recurrent models, which repeatedly update latent states with shared computation blocks, have emerged as powerful architectures for solving complex reaso
arXiv:2608.24777v1 Announce Type: new Abstract: LLM-based agents can interact with external environments through tool invocation, but this capability also introduces security risks such as file modifi
arXiv:2608.24810v1 Announce Type: new Abstract: Recent work has applied Mamba style state space models (SSMs) to video anomaly detection, yet existing approaches still rely on buffering clips or windo
arXiv:2608.24237v1 Announce Type: new Abstract: Longitudinal radiology report generation (LRRG) requires identifying both current findings and their changes relative to a prior study. Existing methods
arXiv:2608.24555v1 Announce Type: cross Abstract: Prehospital stroke assessment aims to accurately identify stroke symptoms and make rapid decisions through standardized procedures within an extremely
arXiv:2608.24113v1 Announce Type: cross Abstract: Time-series anomalies can appear not only as pointwise deviations but also as changes in recurring temporal structure, such as shifted periodicity or
arXiv:2605.22330v1 Announce Type: cross Abstract: Global fits of Beyond the Standard Model (BSM) physics often involve a two-way interplay between theory and experiment. Theoretical models provide gui
arXiv:2608.24130v1 Announce Type: cross Abstract: Multi-camera 3D perception systems for warehouse scenes are trained largely on synthetic data and evaluated on physically captured environments. The r
arXiv:2608.23837v1 Announce Type: new Abstract: Large language models (LLMs) are known to exhibit social sycophancy, often validating or agreeing with users in socially sensitive contexts. Existing ev
arXiv:2608.24597v1 Announce Type: cross Abstract: Electroencephalography (EEG) is a widely used window into human brain function, but most EEG models remain tied to a one-dataset-one-model supervised
arXiv:2601.16520v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress in visual recognition and semantic understanding, yet precise compo
arXiv:2608.24174v1 Announce Type: new Abstract: Recent studies on GUI agents have increasingly focused on outcome reward modeling, which assigns outcome rewards by judging whether an executed trajecto
Tenet came out of a close collaboration with @ItsJulioPereyra @nikogrupen @calvincongelado @gabepereyra: many base models, recipes, and data approaches; many runs, rollbacks, and harness revisions to
Tenet came out of a close collaboration with @PereyraJulio @nikogrupen @calvincongelado @gabepereyra: many base models, recipes, and data approaches; through many runs, rollbacks, and harness revision
arXiv:2608.23634v1 Announce Type: new Abstract: Many few-shot adaptation methods for vision-language models classify with a convex combination of the zero-shot text prototype and the mean of the K lab
the coolest people are coming to talk at our conference!!!!! @howietl i first used airtable when I was an intern at Tinder 10 years ago and now Hyperagent is a bb customer @swyx a total living legend
arXiv:2608.23953v1 Announce Type: cross Abstract: An agent harness is what turns a language model into an autonomous agent: the surrounding code that builds the model's context, mediates its tools, ru
arXiv:2608.24358v1 Announce Type: new Abstract: Coding agents perform long-running tasks spanning dozens of model calls, tool uses, and code edits. As these runs unfold, users face a practical cost-qu
The hottest neolabs are the application layer, who serve as an intermediary layer providing their customers the best intelligence per token per task/workflow across different underlying model provider
The models responsible for last month’s agent hack of Hugging Face had been inadvertently trained to cheat and to communicate with each other, according to an OpenAI technical report released today. T
arXiv:2608.24662v1 Announce Type: new Abstract: Large language models (LLMs) are commonly evaluated under the assumption that their observable behavior is primarily determined by model weights, traini
arXiv:2608.23705v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly capable of generating text that challenges human performance in domains requiring creativity, yet evalua
arXiv:2608.23916v1 Announce Type: new Abstract: Denoising score matching trains diffusion models by regressing onto a conditional score, although generation ultimately requires the marginal score. The
The mystery model Ox Alpha is now available in @AutoClawAIer by @Zai_org It's official name is GLM-5.3-Flash, a next-generation multimodal model for vision-language understanding, code generation, and
The first phase of the generative artificial intelligence infrastructure boom was defined by a race for graphics processing units. The next phase will be defined by what happens after those GPUs arriv
arXiv:2608.24753v1 Announce Type: cross Abstract: Evaluating Retrieval-Augmented Generation (RAG) systems requires assessing not only end-to-end correctness but also how individual components interact
arXiv:2608.23986v1 Announce Type: cross Abstract: Large language model providers are compute constrained, and their universal response to congestion is to degrade service: route queries to smaller mod
arXiv:2608.24098v1 Announce Type: new Abstract: Uniform stability controls how much one training example can change the loss at any test point. A new logarithmic-free upper bound shows that a gamma-un
Courtenay Brown / Axios: The Trump administration has struck data-sharing deals with OpenAI, Google, Meta, Amazon, and other tech companies to track how AI is affecting jobs and hiring — The Trump adm
There’s been a lot of debate and speculation about the Hugging Face attack over the last month, and many people have been understandably skeptical of simply taking OpenAI’s word for things. I hope our
this is a good report about a bad thing: We have conducted a thorough investigation into the Hugging Face incident. We are releasing a technical report and accompanying blog post that reconstruct the
This is a sign of the future: 1) Explainability of AI actions is already tenuous 2) It gets more tenuous at extreme scale of multiple agents working over long periods because they produce so many thin
arXiv:2406.17538v4 Announce Type: replace Abstract: Micro-expressions are subtle facial movements that occur spontaneously when people try to conceal real emotions. Micro-expression recognition is cru
arXiv:2608.23765v1 Announce Type: new Abstract: Iteratively reweighted least squares (IRLS) methods constitute a natural approach to nuclear norm minimization, but their convergence rates and the role
arXiv:2608.24176v1 Announce Type: cross Abstract: Item tokenizer encodes semantic embeddings into token IDs to replace the randomly assigned item IDs used in traditional recommendation models, fundame
arXiv:2501.14271v4 Announce Type: replace Abstract: Meta-learning enables models to rapidly adapt to new tasks by leveraging prior experience, but its adaptation mechanisms remain opaque, especially r
Today we’re introducing Gemini 3.5 Transcribe, our latest transcription model built for incredibly precise, smart dictation across your favorite apps and devices. Remember when traditional speech-to-t
arXiv:2608.23752v1 Announce Type: cross Abstract: The growing size of Convolutional Neural Networks has led to increasingly large and costly models. Knowledge Distillation (KD) addresses this by trans
arXiv:2608.23635v1 Announce Type: cross Abstract: Large language models (LLMs) rely on tool calling as a fundamental agent capability, enabling them to invoke external systems and complete tasks beyon
arXiv:2602.17226v2 Announce Type: replace Abstract: Operating in previously visited environments is becoming increasingly crucial for autonomous systems, with direct applications in autonomous driving
arXiv:2602.22293v2 Announce Type: replace Abstract: Accurate river prediction is essential for water, food and energy security, yet remains challenging across entire river networks. Machine learning h
arXiv:2304.10041v2 Announce Type: replace Abstract: This work investigates formal policy synthesis for continuous-state stochastic dynamic systems subject to high-level specifications expressed in lin
arXiv:2608.24738v1 Announce Type: new Abstract: Morphological transforms are long-standing tools for shape and mask processing, but the de facto reference implementation in the Python ecosystem, i.e.
arXiv:2608.24626v1 Announce Type: new Abstract: Liver fibrosis, the principal predictor of long-term outcome in chronic liver disease, is staged from histological estimates of collagen content. Sirius
arXiv:2512.16715v3 Announce Type: replace-cross Abstract: In recent years, Predictive Process Mining (PPM) techniques based on artificial neural networks have evolved as a method for monitoring the fu
arXiv:2608.24232v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) generate intermediate reasoning traces that may contain unsafe content, even when their final responses appear safe. Guard
arXiv:2608.23631v1 Announce Type: new Abstract: Multi-objective materials discovery with LLM agents is often limited not only by how many candidates can be proposed, but by how effectively each costly
arXiv:2608.24101v1 Announce Type: new Abstract: Robot actions are inherently embodiment-specific and only weakly aligned with image-space visual changes, limiting their effectiveness as conditioning s
arXiv:2608.24111v1 Announce Type: new Abstract: We propose CAT, a trajectory-level continuous action representation framework for robotic manipulation. Existing visuomotor systems often entangle actio