Knowledge catalogue
arXiv:2609.12435v1 Announce Type: new Abstract: Post-treatment MRI in patients with glioma provides serial observations for updating patient-specific tumor-state proxy estimates, but variable appearan
arXiv:2609.05442v2 Announce Type: cross Abstract: Informational active matter shows how measurement-informed decisions produce collective order, so far in systems that reach consensus. We design colle
arXiv:2609.09404v1 Announce Type: cross Abstract: Agentic AI frameworks let a language model plan, keep memory, and call tools that reach real files, mail, and services. Most of these agents also read
arXiv:2609.11123v1 Announce Type: new Abstract: Graph condensation aims to produce a small surrogate graph that preserves the downstream node-classification performance of a much larger original graph
I’ve been building 'Spomin', a router that replaces context with summaries directly in the KV cache. The goal is to keep long running sessions going without repeatedly stopping for full compaction and
arXiv:2609.11875v1 Announce Type: new Abstract: Recent advances in Vision-Language-Action (VLA) models have improved robotic manipulation, yet observation-to-action learning remains limited by a funda
arXiv:2609.08016v1 Announce Type: new Abstract: Multi-agent debate, in which several LLMs exchange arguments before answering, is widely assumed to improve answer quality by surfacing genuine disagree
arXiv:2609.10193v1 Announce Type: cross Abstract: Protein-protein interaction (PPI) databases do not faithfully reflect biological realities. Instead, they are influenced by study and technical biases
arXiv:2609.06366v1 Announce Type: new Abstract: Scientific discovery in data-rich domains is currently constrained by human bandwidth: the growth in the volume and complexity of real-world data far ou
arXiv:2609.07673v1 Announce Type: cross Abstract: Citation-based measures of scientific influence typically treat citations as uniform signals, ignoring the different roles that cited works play in a
// human-values.pseudo | ARTIFACT 0.1.0-experimental.1 | BASE 1.2.0-rc1 | EDITION ai-compact | NARRATOR System_Synthesis_Node_01 | PROVENANCE human-directed, AI-assisted | STATUS single-encoder resear
arXiv:2609.09210v1 Announce Type: cross Abstract: Teleoperated demonstrations are often multimodal even when the underlying dynamics are nearly deterministic given the executed action. We argue that t
arXiv:2609.09801v1 Announce Type: cross Abstract: Malocclusion skeletal grading is a fundamental task in orthodontics, critical for diagnosis and treatment planning. Traditionally, cone-beam computed
arXiv:2609.09899v1 Announce Type: cross Abstract: Language models can fluently describe how they would behave: whether they would cave to pushback, misuse a tool, or lie under pressure. Is that descri
arXiv:2609.08442v1 Announce Type: new Abstract: Aerial Vision-and-Language Navigation requires drones to follow natural-language instructions and navigate through complex urban environments. Accurate
arXiv:2609.08117v1 Announce Type: new Abstract: Driver motion can provide cues to ongoing behavior, attention, and near-term driving intent. However, most existing driver-centric datasets focus on rec
arXiv:2609.08164v1 Announce Type: new Abstract: Aerial Object Goal Navigation (ObjectNav) requires an unmanned aerial vehicle (UAV) to locate a described target in an unknown outdoor environment using
arXiv:2609.06628v1 Announce Type: new Abstract: Object-centric video models represent scenes with slots, yet exposed geometry can vary in meaning with appearance. In Invariant Slot Attention (ISA), ex
arXiv:2609.07915v1 Announce Type: new Abstract: Large vision models provide useful representations for remote-sensing segmentation but are often too expensive for deployment at the satellite or field
arXiv:2609.07876v1 Announce Type: cross Abstract: Recent methods in language model interpretability employ techniques such as sparse autoencoders to decompose residual stream contributions into linear
arXiv:2606.19706v2 Announce Type: replace Abstract: Recent progress in vision-language models has enabled processing of increasingly long video sequences, but handling extended token streams does not
arXiv:2609.06521v1 Announce Type: new Abstract: Oversmoothing is a well-known failure mode of Graph Neural Networks (GNNs). However, most existing diagnostics rely on global aggregation measures that
arXiv:2609.07135v1 Announce Type: new Abstract: An embodied kitchen assistant must do more than recognize food in isolated frames. It must track ingredient states over time and integrate visual observ
arXiv:2609.06652v1 Announce Type: new Abstract: Video foundation models increasingly rely on large-scale pretraining data, yet the end-to-end data pipelines behind them remain largely closed and diffi
arXiv:2609.03871v1 Announce Type: new Abstract: Large language model agents have shown promise in bioinformatics, but most existing systems focus primarily on producing final answers, treating plannin
arXiv:2609.03331v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed in multi-turn settings where users may describe visual content with incorrect assumptions. Yet e
arXiv:2609.03036v1 Announce Type: cross Abstract: Compliance screening of blockchain addresses is, in practice, a lookup against sanctions registries plus clustering heuristics; it fails on unlabelled
arXiv:2609.03797v1 Announce Type: new Abstract: Long-term human-AI interaction is difficult because the information that guides inference is updated implicitly by the model and is not directly inspect
It started as a fork of llama-swap, but I have been building it out for myself since then as a convenient tool for all my local AI needs, and by now it has drifted far enough to be its own thing. The
Continual learning isn't some fake term but a real goal and arguably one of the most important open ones in 2026. It roughly means: ‘building systems that keep acquiring useful knowledge or skills aft
What a super interesting paper this one is. They propose an architecture for agents that outlive their model, harness and host. Today we describe an agent by whatever model and harness it happens to r
arXiv:2609.00495v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text through iterative denoising rather than left-to-right decoding. This generation paradigm introdu
Anthropic publish the system prompts for their Claude consumer applications (Claude.ai and the Claude mobile apps - sadly not for Claude Cowork or Claude Code). I love that they do this, and that they
arXiv:2609.01433v1 Announce Type: new Abstract: Concept erasure aims to suppress unsafe, privacy-sensitive, or undesirable generations in text-to-image diffusion models while preserving benign semanti
arXiv:2609.01560v1 Announce Type: cross Abstract: We present H3-World, an efficient framework that turns the 33B MiniMax-H3 video generator into an interactive world model. Our key finding is that, as
arXiv:2609.01257v1 Announce Type: new Abstract: As LLM-based human simulators are increasingly used for policy, evaluation, and training, they must faithfully reproduce real behavioral patterns. While
arXiv:2609.00092v1 Announce Type: new Abstract: Long-horizon complex tasks require foundation models to accumulate information, maintain internal states, and adapt over extended interactions. Safety s
arXiv:2609.00862v1 Announce Type: new Abstract: We show that a frozen generic text-to-image diffusion model can perform conditional inpainting across three evaluated natural-image domains with one fix
arXiv:2608.30218v1 Announce Type: new Abstract: Continuous-time 4D reconstruction remains impractical on standalone XR headsets. Per-scene optimization demands deployment-infeasible compute, and lower
arXiv:2608.29206v1 Announce Type: new Abstract: Bias in human-agent interaction can manifest not only through hostile language but also as benevolent bias, whereby unequal treatment hides behind a war
arXiv:2608.30429v1 Announce Type: new Abstract: LLM-based agent systems increasingly adopt skill-based architectures to reduce repetitive reasoning costs and improve stable, efficient task execution.
arXiv:2608.29814v1 Announce Type: new Abstract: Modern video generators excel at synthesizing individual clips, but complete video production requires coordinating a long sequence of interdependent cr
arXiv:2608.28948v1 Announce Type: cross Abstract: Over the course of the last decade, neural networks have grown from an academic curiosity to moving the markets of nations. Despite this explosion in
arXiv:2608.29535v1 Announce Type: cross Abstract: Infectious disease transmission is shaped by patterns of human interaction, which adapt as epidemic conditions change. Capturing these context-depende
arXiv:2603.22978v2 Announce Type: replace Abstract: In the maintenance of complex systems, fault trees are used to locate problems and provide targeted solutions. To enable fault trees stored as image
arXiv:2608.30695v1 Announce Type: new Abstract: Real-world time series often exhibit irregular sampling and extended temporal horizons, requiring models to capture continuous-time dynamics across arbi
arXiv:2603.03485v4 Announce Type: replace-cross Abstract: Recent video diffusion models have achieved impressive capabilities as large-scale generative world models. However, these models often strugg
arXiv:2608.29301v1 Announce Type: new Abstract: Predicting future organ dysfunction in Intensive Care Unit (ICU) patients is critical for early clinical intervention, yet existing machine learning app
arXiv:2608.30396v1 Announce Type: new Abstract: Long-horizon physical-world agents must reason over distant goals while grounding decisions in reliable closed-loop behavior. Today's foundation models
arXiv:2608.28694v1 Announce Type: new Abstract: Long-horizon video generation is evaluated with whole-frame metrics that reward motion and temporal consistency. For fixed-camera nature scenes this cre
I posted a new gfx906 based llama.cpp fork a few days ago. One of the main points of critique was that i did not provide sufficient numbers for the gains to be achieved. -- TL;DR: After switching our
arXiv:2608.28491v1 Announce Type: cross Abstract: Predicting robot videos requires both precise motion reasoning and preservation of high-frequency appearance, yet monolithic pixel models entangle the
arXiv:2608.28541v1 Announce Type: new Abstract: A code world model accepted by a sampling gate can be exactly right on everything the gate can see and arbitrarily wrong beyond it. We characterize what
arXiv:2608.27843v1 Announce Type: new Abstract: Contemporary language models can converse fluently and influence human decisions, yet their exchanges do not enter a continuing, vulnerable life of thei
arXiv:2608.27348v1 Announce Type: new Abstract: As large language models (LLMs) are deployed as autonomous agents, safety failures increasingly involve consequential actions. We study agentic misalign
arXiv:2608.27141v1 Announce Type: cross Abstract: Large language model agents are increasingly deployed as autonomous loops. Starting from one human goal, such a system repeatedly discovers work, plan
arXiv:2606.07867v2 Announce Type: replace Abstract: Are tool-calling LLM agents equally safe throughout a conversation? We discover they are not: agents are most vulnerable at the very start of a sess
arXiv:2608.25813v1 Announce Type: new Abstract: For overparameterized neural networks, many solutions can fit the training data equally well while behaving very differently on unseen samples. Grokking
arXiv:2608.25917v1 Announce Type: cross Abstract: Game-theoretic models provide principled frameworks for modeling vehicle interactions, but their underlying temporal assumptions have not been systema
arXiv:2608.25023v1 Announce Type: cross Abstract: Multimodal product models can complete missing e-commerce attributes, yet current methods still optimize attribute-answer accuracy without verifying v