Knowledge catalogue
Learn how I modernized an old codebase of mine using stacked sessions and pull requests in the GitHub Copilot app. The post Stacked sessions and pull requests in the GitHub Copilot app appeared first
Starting in 15 minutes Kimi K3 has everyone’s attention. On July 30, hear @Kimi_Moonshot's Feihu Tang explain the architecture and decisions behind it. He joins Jue Wang and Zain Hasan from Together A
arXiv:2607.26754v1 Announce Type: new Abstract: Recent game world models can generate visually realistic and interactive environments conditioned on player actions. However, games are not defined by p
arXiv:2512.18072v3 Announce Type: replace Abstract: Conversation is a cornerstone of social connection and is linked to well-being outcomes. Conversations vary widely in type with some portion generat
arXiv:2607.26228v1 Announce Type: new Abstract: Instruction hierarchies are a core safety assumption of language model deployment: higher priority inputs, such as system prompts, should override confl
arXiv:2607.27087v1 Announce Type: new Abstract: Anterior eye segment (AES) segmentation is a key component of both ocular biometrics and emerging clinical image analysis applications. However, heterog
arXiv:2602.11219v2 Announce Type: replace Abstract: Predictive uncertainty is commonly decomposed into epistemic and aleatoric components, but standard decompositions often produce strongly correlated
arXiv:2607.26889v1 Announce Type: cross Abstract: Reconstructing articulated objects with multiple movable parts is essential for understanding object structure and enabling physical interaction. Howe
sure we lose money on every inference but we make it up in volume We are committed to pushing the model frontier across cost efficiency, capability, and speed. Starting today, we are reducing prices f
arXiv:2607.26940v1 Announce Type: new Abstract: Ensembles are a standard way to improve the performance and robustness of deep neural networks, but their effectiveness crucially depends on both the qu
arXiv:2607.26985v1 Announce Type: cross Abstract: Deep reinforcement policy learning directly in physical robots (on-robot learning) remains bottlenecked by slow wall-clock training times. We present
arXiv:2607.26355v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly embedded in everyday life and widely used for information seeking, raising concerns about their potential
arXiv:2504.17901v3 Announce Type: replace Abstract: Task and motion planning (TAMP) is a well-established approach for solving long-horizon robot planning problems. Although TAMP methods have historic
arXiv:2607.26924v1 Announce Type: new Abstract: Recent work on LeWorldModel (LeWM) has shown that the Sketched Isotropic Gaussian Regularizer (SIGReg) enables stable end-to-end world-model learning fr
arXiv:2509.05130v2 Announce Type: replace Abstract: In classification problems, models are trained to predict a class label based on the input data features. However, class labels are organized hierar
// The agent is its own best speculator // Agents spend a large share of wall-clock time waiting on tool results. Speculation hides that latency by predicting and pre-executing the next call, but exte
arXiv:2607.26523v1 Announce Type: new Abstract: We introduce CMP (Cognitive Memory Primitive), a continual-learning architecture that repre?sents inputs as sparse relational codes, stores them in a tw
arXiv:2607.26309v1 Announce Type: cross Abstract: Estimating causal effects of linguistic properties from observational text is difficult because the same document can contain both the treatment of in
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. A fundamental flaw leaves LLMs strikingly vulnerable to attack
The narrative: Blame the Agent, instead of the Agency that told him to “apply all your powers and told to achieve this win.” Ironically, many forefront members of the AI-Safety community, in their fer
arXiv:2503.10647v2 Announce Type: replace Abstract: This study evaluated the diagnostic reliability of two Large Language Models (LLMs), Google Gemini 2.0 Flash and OpenAI ChatGPT-4o, across three dim
arXiv:2603.05710v2 Announce Type: replace-cross Abstract: AI development's current trajectory risks automating and amplifying the North-South divide in the global climate information system. Frontier
arXiv:2607.26648v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) are promoted as an energy-efficient substrate because sparse, event-driven activity replaces dense multiply-accumulates
arXiv:2607.26865v1 Announce Type: cross Abstract: LLM agents following the ReAct paradigm are promising enablers of complex multi-step tasks, including multi-hop question answering, code generation, a
Thinking Machines just released Inkling-Small: 276B total, 12B active. A faster Inkling that matches or beats its 975B big brother in many benchmarks. To test its speed, we plugged it into HF's speech
arXiv:2607.26845v1 Announce Type: new Abstract: Inference-time thinking improves the performance of large language models, but aggregate outcomes do not reveal whether models use available evidence mo
This is absolutely wild... Anthropic reviewed their logs and found out that their own supposedly-sandboxed cyber evals had hacked three separate companies back in April without them noticing! In a rev
arXiv:2607.26838v1 Announce Type: new Abstract: In this paper we show that the generalization error of AdaBoost is Thetaig(frac{dln(ngamma^{2}/d)}{ngamma^2}+frac{ln(1/elta)}{n}ig), where gamma is the
arXiv:2607.26383v1 Announce Type: cross Abstract: Cable-driven manipulators exhibit strong nonlinearities and low structural stiffness, which make precise control challenging under time-varying uncert
arXiv:2603.09971v2 Announce Type: replace Abstract: We present TiPToP, a modular manipulation system that integrates pretrained foundation models with a GPU-accelerated Task and Motion Planner to solv
arXiv:2607.26273v1 Announce Type: new Abstract: We consider a stochastic multi-objective bandit problem where, at each round, the agent selects a slate of k arms and observes their d-dimensional rewar
arXiv:2607.27122v1 Announce Type: new Abstract: Gastrointestinal (GI) endoscopic image analysis has shifted from single-label classification toward visual question answering (VQA), where a model must
arXiv:2607.26121v1 Announce Type: new Abstract: Embodied intelligence integrates learned perception and decision making with real-time computation, control, and physical interaction. Because failures
arXiv:2607.26849v1 Announce Type: cross Abstract: As large language models (LLMs) are deployed in high-stakes domains, adversaries may poison training data to implant backdoors: hidden triggers that c
arXiv:2607.26536v1 Announce Type: new Abstract: High-pressure prompts can push vision-language models (VLMs) into unsupported commitments, such as reading illegible text, reporting indeterminate times
arXiv:2607.26706v1 Announce Type: new Abstract: Text-to-video diffusion models generate temporally coherent content from natural language, yet when a prompt describes an early scene that persists whil
arXiv:2607.26107v1 Announce Type: new Abstract: Dense vision-language understanding, including object localization, region recognition, and open-vocabulary semantic segmentation, requires associating
arXiv:2510.00192v3 Announce Type: replace Abstract: Low-rank adaptation (LoRA) has become a widely used paradigm for parameter-efficient fine-tuning of large language models, yet its representational
arXiv:2603.17019v2 Announce Type: replace Abstract: A central question in the debate over large language models is whether transformers can learn rules they have never seen, or whether they can only i
arXiv:2607.26854v1 Announce Type: new Abstract: Accurate multi-week dengue forecasting supports timely vector-control interventions, outbreak preparedness, and healthcare resource allocation. However,
arXiv:2607.27027v1 Announce Type: new Abstract: Gradient-boosted trees dominate tabular machine learning, yet canonical correlation analysis has always relied on linear or neural encoders. We propose
arXiv:2607.26977v1 Announce Type: new Abstract: Travel planning is a demanding stress test for tool-using LLM agents: a usable itinerary is a single artifact that must be right along many axes at once
arXiv:2607.26117v1 Announce Type: cross Abstract: Self-repair - returning a failed program to the model together with its test output and asking for a correction - is a standard component of code agen
Its a custom Swift/Metal inference engine that runs Gemma 4 26B-A4B-IT on M-series Macs with very low RAM. It uses ~2GB instead of ~14 GB. The result is reportedly 5–6 tok/s on an 8 GB M2 MacBook Air
arXiv:2607.27205v1 Announce Type: new Abstract: Vision-language-action (VLA) models commonly adopt an LLM-centric V o L o A pathway, where visual observations are projected into the representation spa
arXiv:2607.26922v1 Announce Type: new Abstract: Multi-agent LLM pipeline systems break down the task among multiple roles for better reasoning, but are benchmarked mainly with large-scale commercial m
arXiv:2607.26108v1 Announce Type: cross Abstract: Realistic animal motion for virtual production is typically obtained either through motion capture of highly trained performers who accurately mimic a
arXiv:2607.26599v1 Announce Type: new Abstract: Estimating heterogeneous treatment effects is central to targeted interventions, such as personalized promotions and precision medicine. We focus on the
DigitalOcean launched Kimi K3 on day 0. It’s already one of the most popular models on the platform and across the market: second most likes on Hugging Face, sixth most traffic on OpenCode. Getting a
arXiv:2607.26628v1 Announce Type: new Abstract: TabPFN performs classification through in-context learning: it conditions on a set of labeled training rows (the context, or prototypes) and predicts te
arXiv:2607.26608v1 Announce Type: new Abstract: Training-free fusion of heterogeneous multimodal large language models (MLLMs) provides a direct route for cross-scale capability transfer, yet improvem
arXiv:2607.26699v1 Announce Type: new Abstract: We investigate message-passing graph neural networks with random node features. Random node features are known to enhance the expressiveness of graph ne
Are there any benchmarks on these 4 bit quants, like how Artificial Analysis runs a slew of various benchmarks? If not, how can I run one (5x over for consistency) on them? I'm also very interested in
arXiv:2607.26984v1 Announce Type: cross Abstract: Mapping an atomic structure to a compact set of geometric descriptors is an essential step in any machine-learning application to atomic-scale modelin
arXiv:2606.18426v2 Announce Type: replace Abstract: We introduce VEGA, an approach for training navigation VisionLanguage-Action (VLA) models from unlabeled egocentric navigation videos. Internet-scal
arXiv:2607.27113v1 Announce Type: new Abstract: The growing capability of image generation models has made synthetic images a routine presence in open media, making robust and generalizable AI-Generat
arXiv:2510.08543v2 Announce Type: replace-cross Abstract: As Video Large Language Models (VideoLLMs) are deployed globally, it is important to assess their ability to reason across cultural contexts.
arXiv:2607.27194v1 Announce Type: new Abstract: Accurately recovering the camera's calibration and metric poses for any unconstrained video would unlock large-scale training data for navigation and sc
arXiv:2512.01280v2 Announce Type: replace Abstract: Autonomous aerial tracking with drones offers vast potential for surveillance, cinematography, and industrial inspection applications. While single-
arXiv:2607.26770v1 Announce Type: new Abstract: Temporal logic (TL) provides a compositional language for the formulation of long horizon robotic tasks, but existing TL-conditioned trajectory generato