Knowledge catalogue
arXiv:2608.25872v1 Announce Type: new Abstract: Contact-rich manipulation requires precise interaction feedback. While vision-centric imitation learning is prevalent, external visual observations prov
arXiv:2608.24940v1 Announce Type: new Abstract: Partial differential equations (PDEs) often have high-frequency and multi-scale features that neural networks struggle to approximate. Physics-Informed
Forgive the typos and rambling - human actually wrote this post 😂 I've had a Strix Halo board for about a year and been playing around with it for various projects when it's not just being a beefy lin
arXiv:2608.24229v1 Announce Type: cross Abstract: Quantum noise is expected to degrade quantum machine learning by driving circuits away from their noiseless implementations. Yet recent studies show m
arXiv:2608.24372v1 Announce Type: new Abstract: AI-generated image quality assessment (AIGIQA) requires jointly reasoning about perceptual fidelity and prompt alignment, two quality dimensions that ar
arXiv:2608.24545v1 Announce Type: new Abstract: Human collective intelligence depends on transmission processes: who shares what with whom, how, and when. While these processes emerge from individual
arXiv:2608.24572v1 Announce Type: new Abstract: Capturing hand pose during dexterous manipulation remains difficult: vision-based methods degrade under occlusion and challenging lighting, while sensor
arXiv:2608.24547v1 Announce Type: new Abstract: Simulation is central to modern engineering and science, but the cost of numerical solvers for partial differential equations (PDEs) remains a bottlenec
arXiv:2608.24368v1 Announce Type: new Abstract: Reliable multi-turn tool use requires an agent to preserve an evolving task state and ensure that each action remains consistent with it. However, direc
arXiv:2608.24603v1 Announce Type: new Abstract: Vision language action models (VLAs) have advanced general purpose robotic grasping and manipulation by enabling robots to interpret visual observations
arXiv:2608.24541v1 Announce Type: new Abstract: Surgical instrument segmentation (SIS) is fundamental for computer-assisted surgery, where reliable instrument masks enable precise scene understanding
arXiv:2402.01767v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) significantly improves document-based question answering by integrating external documents during generat
arXiv:2608.24588v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly solve long-horizon tasks through multi-turn interactions with users and external tools. In these settings
Hi everyone, it's been a while since I posted so here's an update on what the Lemonade community has been up to this summer. Our overall mission is to enable local AI builders with everything they nee
arXiv:2608.23982v1 Announce Type: new Abstract: Scientific reasoning requires language models to retrieve specialized knowledge and incorporate it reliably into multi-step computation. Conditional mem
arXiv:2608.23834v1 Announce Type: new Abstract: The key-value (KV) cache is a primary capacity and bandwidth bottleneck in long-context LLM serving. We present Minima-KV, a retention-preserving hierar
arXiv:2608.24783v1 Announce Type: new Abstract: Accurate segmentation of coronary arteries in X-ray angiography videos is essential for quantitative coronary analysis and image-guided interventions. H
arXiv:2608.23646v1 Announce Type: new Abstract: Molecular embedding models can serve as foundational infrastructure for computational chemistry and drug discovery, where reusable vector representation
arXiv:2608.23897v1 Announce Type: cross Abstract: When a code generating language model fabricates a Python package name, an adversary who has pre-registered that name on PyPI can convert that halluci
So here's the thing, almost everyone use NVIDIA to run their LLMs, we also do the same, a lot of people we've met use like RTX PRO 6000 or even H100, B300 It seems like everyone eyes is looking at NVI
arXiv:2608.23790v1 Announce Type: new Abstract: How does an intelligent visual system combine what objects look like with how they move while remaining robust as appearance changes? We addressed this
arXiv:2608.23956v1 Announce Type: new Abstract: Test-time reasoning methods such as iterative refinement, decomposition, and repeated sampling are often evaluated in isolation, making their gains diff
arXiv:2608.23696v1 Announce Type: new Abstract: Despite their remarkable success in modeling complex data, generative models face a fundamental tradeoff. Global approaches can capture full structural
arXiv:2509.15959v2 Announce Type: replace-cross Abstract: Autonomous navigation in maritime domains is accelerating alongside advances in artificial intelligence, sensing, and connectivity. Opaque dec
arXiv:2608.24338v1 Announce Type: new Abstract: Inference-time decoding methods improve LLM reasoning by exploring multiple candidate trajectories, yet treat each trajectory as atomic: either retainin
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: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
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
arXiv:2608.23582v1 Announce Type: cross Abstract: We present the Transformer Accelerator (TFA), a synthesizable, parameterizable INT8 memory-to-memory engine for transformer inference. One time-multip
arXiv:2608.24119v1 Announce Type: cross Abstract: Visual demonstrations provide a natural interface for specifying image transformations that are difficult to describe exhaustively with text. However,
arXiv:2608.24366v1 Announce Type: new Abstract: End-to-end multimodal driving has progressed rapidly by fusing camera and LiDAR streams. Existing pipelines remain fragile under asymmetric sensor degra
What happens when there are more agents than eyeballs browsing the internet? How will the economics of the internet be reinvented? @paraga thinks Shapley values may hold the answer. Parag built Twitte
arXiv:2606.13705v2 Announce Type: replace-cross Abstract: The Gemma 4 instruction-tuned models share a reproducible failure: on long factual enumeration prompts, such as TV episodes, the 88 IAU conste
arXiv:2608.21423v1 Announce Type: cross Abstract: Agentic security uses large-language-model (LLM) agents to plan, dispatch, and interpret security tools. As these systems move from demonstrations to
arXiv:2608.21894v1 Announce Type: new Abstract: Human tactile perception relies on complex multisensory cues. Yet the relationship between tactile signals and perceptual representations remains poorly
arXiv:2608.21747v1 Announce Type: cross Abstract: LLM-based coding agents generate complete software systems from high-level descriptions, yet little is known about how the format of architecture spec
arXiv:2608.23263v1 Announce Type: new Abstract: The FAIR Digital Object (FDO) framework mandates that metadata attribute values be expressed as persistent identifiers (PIDs) wherever possible, to prod
arXiv:2608.21503v1 Announce Type: cross Abstract: A verification substrate is more credible when exposing errors in its own claims, not just model outputs. GBI-DCSE v3 falsified an architectural claim
arXiv:2608.21447v1 Announce Type: new Abstract: Structured-language models such as SceneScript reconstruct a scene as a short program of parametric commands, an inherently editable and semantically ex
arXiv:2608.21937v1 Announce Type: new Abstract: Incremental Object Detection (IOD) aims to enable detectors to continuously learn novel categories while preserving previously acquired knowledge. Howev
arXiv:2608.21899v1 Announce Type: new Abstract: Human-in-the-loop real-world reinforcement learning enables rapid acquisition of effective robotic manipulation policies for individual tasks, often wit
arXiv:2608.22074v1 Announce Type: cross Abstract: Identifying atomic defects at elevated temperature is difficult because thermal fluctuations blur the local symmetry that both geometric heuristics an
arXiv:2608.22770v1 Announce Type: new Abstract: Financial institutions need an independent way to detect missing, stale, and misclassified corporate-event records in vendor databases. We introduce Sea
arXiv:2608.22368v1 Announce Type: new Abstract: While linear attention is a compelling mechanism for high-resolution object detection due to its reduced cost for global token mixing, converting the So
arXiv:2608.22014v1 Announce Type: new Abstract: Automated prompt and skill optimization typically produces a single static instruction that is reused across inference instances until the next optimiza
arXiv:2606.17642v3 Announce Type: replace Abstract: Financial multimodal reasoning requires agents to coordinate numerical computation, retrieval, visual interpretation, and temporal grounding across
arXiv:2508.05078v2 Announce Type: replace-cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) is essential for adapting Large Language Models (LLMs) to multi-task scenarios. A prevailing trend in t
arXiv:2608.22055v1 Announce Type: new Abstract: Suppose one embodied agent knows what must be built, while its teammate alone knows which transformation its workcell can perform. Neither local view de
arXiv:2608.21868v1 Announce Type: new Abstract: Depression assessment from multimodal clinical interviews requires integrating dispersed evidence from multiple symptoms into a coherent PHQ-8 profile.
If you keep safety rules or coding standards in an AGENTS.md or a CLAUDE.md, this one is worth your time. (bookmark it) Researchers measured what context compaction actually destroys across 20 product
Building a local AI agent hierarchy on a budget — RAG, quantization, and testing whether fact-grounding pushes small models toward real creativity I don't have a CS background, a GPU, or much of a bud
arXiv:2608.22631v1 Announce Type: new Abstract: Terminal agents are a compelling application of large language models (LLMs), with the potential to integrate deeply into users' daily workflows. Reinfo
arXiv:2505.14240v3 Announce Type: replace Abstract: Integrating combinatorial optimization layers into neural networks has recently attracted significant research interest. However, many existing appr
arXiv:2608.21501v1 Announce Type: new Abstract: Credit assignment in large-language-model reinforcement learning (LLM RL) can be separated into three objects: evidence about success, a transport opera
arXiv:2509.23705v2 Announce Type: replace Abstract: Multi-robot coverage path planning commonly balances geometric area or path length under a constantspeed assumption. This assumption is inadequate w
arXiv:2608.21554v1 Announce Type: cross Abstract: Heterogeneous multi-robot service systems must assign requests to compatible robots, construct feasible schedules, and adapt as new tasks arrive onlin
arXiv:2608.23086v1 Announce Type: new Abstract: Black-box large language models need confidence scores that can separate likely-correct from likely-incorrect outputs, enabling systems to prioritize hu
arXiv:2508.17440v3 Announce Type: replace-cross Abstract: Photonic processors are naturally suited to linear transformations, but independently programmable higher-order interactions usually require n
arXiv:2608.21597v1 Announce Type: cross Abstract: Clinical data sources such as electronic health records and wearable sensors record patient status repeatedly over follow-up, often at irregular times
arXiv:2608.22329v1 Announce Type: cross Abstract: Emotion-aware artistic image generation requires a model to satisfy semantic content, artistic style, and target emotion simultaneously. The key chall