Knowledge catalogue
Meir Orbach / CTech: Nasdaq-listed neocloud Nebius acquires Inferize, whose tech helps optimize GPU utilization and reduce AI request costs, sources say for 100M to 150M — The Israeli startup, which w
arXiv:2609.00377v1 Announce Type: cross Abstract: We present FoldingAgent, an agentic framework for inferring explicit parametric folding programs directly from origami demonstration videos. Our frame
Most extraction tools treat spreadsheets like PDFs. They flatten the file into text or markdown, then ask a model to infer the original structure. But spreadsheets depend on structure. Headers, formul
arXiv:2409.18073v2 Announce Type: replace-cross Abstract: For AI agents to be helpful to humans, they should be able to follow natural language instructions to complete everyday cooperative tasks in h
arXiv:2608.22067v1 Announce Type: cross Abstract: World-Action Models (WAMs) build robot control on video-generation backbones, which jointly predict dense future visual trajectories and robot actions
OpenAI’s Jalapeño is a self‑designed ASIC for large‑language‑model inference that was taped‑out in about 16 months, developed with Broadcom and featuring HBM4 memory. Benchmarks on the InferenceX suit
arXiv:2603.00056v2 Announce Type: replace-cross Abstract: STEM Mental models can play a critical role in assessing students' conceptual understanding of a topic. They not only offer insights into what
arXiv:2510.15127v3 Announce Type: replace-cross Abstract: Identifying the effects of mechanical ventilation (MV) protocols in critical care requires analyzing data from heterogeneous patient-ventilato
arXiv:2607.25516v1 Announce Type: new Abstract: Vision-language-action (VLA) models predict sequential actions to execute tasks specified by language instructions, conditioned on visual observations a
arXiv:2607.04501v1 Announce Type: cross Abstract: The ability to automatically infer analytic intent from user interaction histories could enable interactive AI systems to proactively assist users dur
arXiv:2508.08983v2 Announce Type: replace-cross Abstract: Humans can learn a new manipulation task from one or two demonstrations and then perform it in a new room, with new objects, under new constra
arXiv:2607.02402v2 Announce Type: replace Abstract: Vision-language models (VLMs) can follow complex textual instructions, yet they struggle to reason from purely visual context. In particular, curren
arXiv:2607.03598v1 Announce Type: cross Abstract: When a person shares something with a language model, the model often answers the surface of the message rather than what the sender was doing by send
Nemotron 3 Ultra (550B-A55B) is here - our strongest open-weight model and full training recipe to date. Heavy emphasis on real-world inference efficiency for long-context agentic workloads. Everythin
arXiv:2606.04468v1 Announce Type: cross Abstract: Offline multi-objective optimization (Offline MOO) aims to discover novel Pareto-optimal designs based on static datasets without expensive environmen
Build on-device personal AI agents on Windows PCs with new tools from NVIDIA and Microsoft, including secure sandboxing, faster local inference, multi-GPU support, and RTX acceleration for Windows AI
Perplexity AI demonstrates a hybrid approach to AI inference that combines on-device processing for sensitive data with cloud-based AI services to achieve scalability and contextual understanding. Thi
arXiv:2606.01845v1 Announce Type: cross Abstract: Although large language models (LLMs) have shown considerable progress in pragmatic language understanding, prior research has focused mainly on their
arXiv:2503.05641v4 Announce Type: replace-cross Abstract: Combining existing pre-trained LLMs is a promising approach for diverse reasoning tasks. However, task-level expert selection is often too coa
arXiv:2510.23905v2 Announce Type: replace-cross Abstract: This paper studies group target trajectory intent as the outcome of a cooperative game where the complex-spatio trajectories are modeled using
arXiv:2510.24680v2 Announce Type: replace Abstract: While imitation learning (IL) has enabled successful visual navigation in many common environments, IL policies are prone to unpredictable failures
Yohei Nakajima analyzed OpenAI's 663 open job positions using ChatGPT to identify patterns and infer insights about the company's strategic direction and priorities. While the analysis didn't reveal g
This post likely discusses a cognitive or computational principle where one should primarily focus on horizontal (broad, general, or foundational) aspects of a problem or system, then use inference or
We've teamed up with @cerebras to offer free Windsurf plans for SWE-1.6 Fast Mode at up to 1000 tok/s! Fast Mode is built on Cerebras inference, enabling superior speed for planning and development wi
arXiv:2605.04454v1 Announce Type: cross Abstract: Alignment evaluation in machine learning has largely become evaluation of models. Influential benchmarks score model outputs under fixed inputs, such
Ambient diffusion was a really cool paper in this space. Given corrupted data, corrupt even further, such that the model can’t infer what was genuine corruption vs synthetically added. In expectation
arXiv:2604.19785v1 Announce Type: cross Abstract: Sensitive information, such as knowledge about an individual's personality, can be can be misused to influence behavior (e.g., via personalized messag
arXiv:2508.13792v2 Announce Type: replace Abstract: The intrinsic dynamics of an object governs its physical behavior in the real world, playing a critical role in enabling physically plausible intera
OpenClaw 2026.4.7 🦞 🔮 openclaw infer 🎬 music + video editing 💾 session branch/restore 🔗 webhook-driven TaskFlows 🤖 Arcee, Gemma 4, Ollama vision 🧠 memory-wiki: persistent knowledge, not just vibes Bec
arXiv:2606.17688v2 Announce Type: replace Abstract: Recent work has shown that LLMs overrepresent dominant cultures, particularly Western ones, while marginalizing others. We investigate whether this
arXiv:2610.01786v1 Announce Type: new Abstract: Neural activity often exhibits multiple timescales that can vary with behavioral states and task conditions. Identifying these timescales from neural re
arXiv:2609.35827v2 Announce Type: cross Abstract: The quality of a detector design is ultimately determined by the quality of the inference it enables, that is, by the accuracy with which the quantiti
arXiv:2609.30074v1 Announce Type: cross Abstract: Evaluations of LLM systems routinely average over small prompt sets and report models as a ranked table. We ask how much confidence such a table deser
Compute (EC2) opened the front door to the first generation cloud. Agents need something different: compute, inference, and data working as one. We built the cloud that delivers all three as one simpl
arXiv:2609.07139v1 Announce Type: new Abstract: A transformer can make an attribute linearly decodable in its residual stream at a depth where that attribute does not yet influence the output. This ga
arXiv:2609.07349v1 Announce Type: new Abstract: Real-time urban governance depends not only on knowing where people are, but on how they move between places, directional flows that could be convention
arXiv:2609.03422v1 Announce Type: new Abstract: Diversity is a widely observed factor in the resilient function of collective systems, yet the type of diversity that matters depends on the properties
arXiv:2608.30773v1 Announce Type: new Abstract: In animals such as elephants and octopuses, acquiring non-visual information about an object and physically engaging with it are inseparable processes m
arXiv:2504.02839v2 Announce Type: replace-cross Abstract: Proteins move and deform to ensure their biological functions. Despite significant progress in protein structure prediction, approximating con
arXiv:2606.03371v1 Announce Type: new Abstract: Multimodal retail agents should not only recognize what a customer is doing, but also decide whether and how to assist before an explicit request is mad
arXiv:2503.14190v3 Announce Type: replace Abstract: A common goal in analyzing time series data is to understand how events cause observed variations. We study whether Large Language Models (LLMs) can
arXiv:2605.29223v1 Announce Type: new Abstract: The parameter counts of the most widely used large language models (LLMs) are often withheld by their developers, leaving model size -- a primary refere
arXiv:2605.19644v1 Announce Type: cross Abstract: Knowledge Graphs (KGs) are a powerful representation of linked data, offering flexibility, semantic richness, and support for knowledge enrichment and
arXiv:2604.27633v1 Announce Type: new Abstract: Large language models (LLMs) are commonly evaluated for political bias based on their responses to fixed questionnaires, which typically place frontier
arXiv:2604.21793v1 Announce Type: new Abstract: In this paper, we develop a novel logic-based approach to detecting high-level temporally extended events from timestamped data and background knowledge
arXiv:2604.12461v1 Announce Type: new Abstract: LLM-based Multi-Agent Systems (MAS) have demonstrated remarkable capabilities in solving complex tasks. Central to MAS is the communication topology whi
Auto-generated index of all models mentioned across the wiki.
arXiv:2610.14577v1 Announce Type: new Abstract: During human-robot interaction, sight plays an important role. When the human sees a robot, they can observe the robot's actions and better predict the
arXiv:2609.14173v1 Announce Type: new Abstract: Human-to-robot skill transfer from sensing gloves has so far relied on shared hardware: the same tactile glove worn by the demonstrator and the robot, o
arXiv:2609.14660v1 Announce Type: cross Abstract: Split computing constitutes a widely used distributed inference approach, where a lightweight head model is onloaded onto the device and a heavier tai
arXiv:2608.08064v1 Announce Type: new Abstract: Learning fine-grained spatial patterns from coarse-resolution data is challenging, especially in causal settings where high-resolution effects must be i
As a market leader in enterprise agentic automation and business orchestration, UiPath is helping to pioneer an industry shift toward agentic AI. With it, the company is deploying autonomous agents to
arXiv:2607.12696v1 Announce Type: cross Abstract: Sparse Mixture-of-Experts (MoE) models have become an important approach for scaling Large Language Models (LLMs), but their inference efficiency depe
arXiv:2605.27950v1 Announce Type: new Abstract: Accurately assessing dietary behavior change receptivity is essential for designing effective just-in-time adaptive interventions (JITAIs) that promote
arXiv:2509.19538v2 Announce Type: replace-cross Abstract: Diffusion-based world models have demonstrated strong capabilities in synthesizing realistic long-horizon trajectories for offline reinforceme
arXiv:2605.12178v1 Announce Type: cross Abstract: World models enable agents to anticipate the effects of their actions by internalizing environment dynamics. In enterprise systems, however, these dyn
arXiv:2605.03247v1 Announce Type: new Abstract: Neural PDE simulators often receive only a single observed field at deployment. In this setting, a field-to-future predictor can collapse distinct laten
While generative AI sparked a revolution, the true paradigm shift is the rapid evolution from standalone AI models to multi-agent autonomous systems. In this new era, the network transcends basic conn
arXiv:2603.22564v2 Announce Type: replace Abstract: Understanding cellular trajectories via time-resolved single-cell transcriptomics is vital for studying development, regeneration, and disease. A ke
arXiv:2604.11020v1 Announce Type: new Abstract: We investigate estimating a human's world belief state using a robot's observations in a dynamic, 3D, and partially observable environment. The methods