Knowledge catalogue
arXiv:2610.13479v1 Announce Type: new Abstract: Generating edge case scenarios is crucial for training, testing and safety assuring autonomous systems. This identifies hazardous failures to increase s
arXiv:2610.13744v1 Announce Type: new Abstract: On-policy self-distillation promises to replace the sparse outcome signal of verifiable-reward RL with dense token-level credit: a teacher conditioned o
arXiv:2603.03753v2 Announce Type: replace-cross Abstract: The ongoing shift of Artificial Intelligence (AI) from centralized cloud application programming interfaces (APIs) to local inference on edge
arXiv:2610.12843v1 Announce Type: cross Abstract: Fewer latent tokens promise cheaper diffusion. Yet aggressive latent compression creates a reconstruction-generation dilemma: adding channels improves
arXiv:2610.13277v1 Announce Type: cross Abstract: Memory-augmented assistants retrieve evidence from stored conversations and documents to answer queries. Most embedding-based retrievers compare singl
arXiv:2610.13113v1 Announce Type: cross Abstract: Continual post-training faces a dual challenge of acquisition and retention: models must learn new capabilities while preserving prior knowledge. Whil
arXiv:2610.12514v1 Announce Type: cross Abstract: Autoregressive video diffusion models maintain a growing attention key-value (KV) cache, making memory a key bottleneck for long video generation. Rec
arXiv:2507.19608v2 Announce Type: replace Abstract: On-device LLM inference is increasingly important for edge platforms but remains challenging due to high computational and memory demands and tight
arXiv:2610.12637v1 Announce Type: new Abstract: We consider hole closure in a planar multi-agent system whose sensing disks form a time-varying Cech complex. We propose a harmonic-covariance feedback
arXiv:2610.13112v1 Announce Type: new Abstract: Large audio-language models (LALMs) frequently exhibit object hallucination, affirming absent sounds. The dominant mitigation, Audio-Aware Decoding (AAD
arXiv:2610.13132v1 Announce Type: new Abstract: LLM-as-a-Service has become a dominant paradigm for accessing large language models without requiring local deployment. However, the process raises seve
arXiv:2610.12796v1 Announce Type: cross Abstract: Audio-visual speech enhancement (AVSE) improves speech intelligibility in noisy environments but often relies on computationally expensive models unsu
arXiv:2610.12541v1 Announce Type: new Abstract: Boundary-value problems for the Laplace equation develop singular behaviour near corners, edges and junctions that smooth approximators resolve poorly.
arXiv:2610.13337v1 Announce Type: cross Abstract: Attention sinks are tokens or positions that consistently receive disproportionate attention mass, often beyond what their semantic content would sugg
arXiv:2610.13035v1 Announce Type: cross Abstract: Multi-view representations enable pretrained image and video vision-language models to understand 3D scenes, but their long visual token sequences mak
arXiv:2601.13600v2 Announce Type: replace Abstract: NLP systems increasingly aggregate claims from retrieved passages, documents, and generated reasoning steps. Yet current factuality methods mostly v
A few weeks ago we posted the open-source Graphsignal profiler here: wrap vllm serve / sglang serve / whatever in graphsignal-run and it serves everything it measures as JSON, mainly so an agent can r
arXiv:2511.01047v4 Announce Type: replace-cross Abstract: Automated program repair (APR) has recently shifted toward large language models and agent-based systems, while prior work shows that reposito
arXiv:2610.13935v1 Announce Type: cross Abstract: Interpreting machine learning model predictions is a central challenge, particularly for black-box vision models. Concept-based attribution methods in
Quick context: LocalLightChat (LLC) is a chat frontend for local LLMs. Download it, run it, that's it. No installation (unless you want to), no dependencies, and it runs on pretty much anything, inclu
arXiv:2610.13717v1 Announce Type: new Abstract: Federated clustering can support applications such as patient stratification across hospitals and customer segmentation across distributed financial dat
arXiv:2610.13794v1 Announce Type: new Abstract: Discourse particles subtly shape the flow of discourse by reflecting conversational context and interlocutor attitudes, often leaving the truth-conditio
arXiv:2610.13373v1 Announce Type: new Abstract: Translating language into humanoid motion requires coordinating body parts, determining motion duration, and producing references suitable for robot exe
arXiv:2610.13557v1 Announce Type: new Abstract: Anticipation of vessel trajectories is an essential task when navigating at sea. This applies to both human navigators and autonomous surface vessels. T
I wanted to track grocery spending per item without sending my receipts to anyone, so I built an Android app around a small vision model that reads a photo of a receipt into JSON: store, date, total,
arXiv:2610.13166v1 Announce Type: new Abstract: Terminal agents are moving beyond local operations toward completing real-world professional tasks. Short trajectories can demonstrate commands and tool
arXiv:2610.12768v1 Announce Type: cross Abstract: Semantic query engines evaluate natural-language filters with a large language model, and every evaluation is a costly oracle call. Optimizers that re
arXiv:2610.12723v1 Announce Type: new Abstract: Neural surrogates that forecast a physical field from sparse, noisy sensors read a window of nearby sensors and a history of past snapshots. Practitione
arXiv:2610.13896v1 Announce Type: new Abstract: Neural semantic parsers generate meaning representations token by token, yet well-formedness depends on references, scope, and graph relations that unfo
arXiv:2610.13020v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a dominant paradigm for enhancing LLMs' reasoning capabilities. Yet long-horizon autoregressive rollouts introduc
arXiv:2508.02161v2 Announce Type: replace Abstract: Trajectory prediction is essential for formulating proactive strategies that anticipate user mobility and support advance preparation. Therefore, ho
I'm trying to figure out the best long-term upgrade path for my setup. Right now my GPUs are spread across several consumer PCs: Main: 5900X, 32GB DDR4, 2× RTX 3090 24GB. Secondary: i3-10320, 16GB DDR
I run local LLMs pretty much around the clock, but I also enjoy gaming on the same PC. Having models sitting in VRAM while gaming isn't exactly ideal, and constantly unloading and reloading them manua
Currently contemplating adding either M5 Ultra 256GB or dual DGX Spark in addition to existing 5090. I have been researching for past few days and have zeroed in on dual sparks because higher throughp
I was curious about how omni decision models could be used in rescue workers bodycams or smart glasses, so I decided to build a quick demo. I went with @liquidai d1-omni-600M since it supports both vi
https://preview.redd.it/uyjw2lcrvkuh1.png?width=1536&format=png&auto=webp&s=ce991be22faec3de5cbaf39119c14782b6ed0af3 link to article TLDR; new microsoft surface and nvidia rtx spark laptops are starti
I am developing a Windows-based local AI virtual spouse application that supports adult roleplay. My goal is to run it without a server or external AI APIs. I am looking for existing open-source modul
https://typesafe.ai/blog/series-ai Meanwhile one of the reddit members apparently developed the same architecture a year ago: https://www.reddit.com/r/LocalLLaMA/s/8zQXqCNDlb Looks like ai valuation n
Hey everyone! 👋 After months of building, we’re finally opening the first spots for **Many Agents**, a new product from Dome. The idea is simple: **What if you could create your own team of AI agents
https://preview.redd.it/7sknv6omnguh1.png?width=1023&format=png&auto=webp&s=4aef1dc464d008b00f104519eb5399ba6132ad69 Want to try? Just go here and click 'New seed' a lot. You will get different storie
arXiv:2610.11527v1 Announce Type: new Abstract: Atomistic simulation is a fundamental tool for studying long-term materials evolution, from diffusion and defect dynamics to interfacial reactions and f
arXiv:2503.06140v3 Announce Type: replace Abstract: Transfer-based attacks pose a significant threat to real-world applications by directly targeting victim models with adversarial examples generated
arXiv:2610.11214v1 Announce Type: cross Abstract: KV-cache quantization and linear attention are two representative approaches to tackling the storage and computational costs of Transformers. KV-cache
arXiv:2610.10974v1 Announce Type: cross Abstract: Off-policy evaluation (OPE) estimates the value of a target policy from logged data, but limited behavior-policy coverage can force high-variance rewe
arXiv:2610.11422v1 Announce Type: cross Abstract: Many dynamical systems generate influences whose consequences are not fully exhausted in the realized trajectory at the moment they arise. Such conseq
arXiv:2511.02147v2 Announce Type: replace Abstract: Collaborating teams of robots show promise due to their ability to complete missions more efficiently and with improved robustness, attributes that
arXiv:2610.11300v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for automated code generation, but generated programs can appear syntactically plausible while stil
arXiv:2405.15662v2 Announce Type: replace Abstract: Machine unlearning aims to remove the influence of specified training data or knowledge from a trained model without requiring full retraining. This
arXiv:2507.13835v2 Announce Type: replace-cross Abstract: The amount of quality data in many machine learning tasks is limited to what is available locally to data owners. The set of quality data can
arXiv:2610.12266v1 Announce Type: cross Abstract: Multimodal large language models have made remarkable progress in bridging vision and language, facilitating various perception tasks essential for hu
arXiv:2604.04611v3 Announce Type: replace Abstract: Federated learning (FL) enables multiple clients to collaboratively train a global model by aggregating local updates without sharing private data.
arXiv:2610.12035v1 Announce Type: cross Abstract: Archetypal Analysis (AA) represents observations as convex combinations of extremal data-driven profiles, yielding interpretable low-dimensional descr
I checked the site, and it didn't say anything about mlx only on the ollama models listing. So why is this restriction in place? ollama pull embeddinggemma-2 pulling manifest Error: this model require
I posted on here a while back asking for advice on upgrading to an Epyc system. Thanks to all who commented. I’ve taken the plunge and ordered: - Epyc 7443 CPU (24 cores, 48 threads, 128 lanes) - H12S
arXiv:2610.11920v1 Announce Type: new Abstract: For persistent and personalized conversational agents, memory systems can enable them to remember, update, and reason over long histories by storing pas
arXiv:2610.11651v1 Announce Type: new Abstract: Automated interviewers and conversational agents are increasingly used in research, recruitment, customer service, and education. However, many existing
arXiv:2610.10998v1 Announce Type: new Abstract: Neural operators enable fast PDE forecasting, but repeated predictions accumulate errors and fine-scale structures remain difficult to resolve. We intro
arXiv:2610.11502v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong reasoning capabilities when fine-tuned with reinforcement learning (RL), particularly through Group Relat
arXiv:2610.11033v1 Announce Type: new Abstract: Multiple institutions may each hold their own private knowledge edits and wish to integrate them into a single large language model without sharing raw
arXiv:2610.11318v1 Announce Type: new Abstract: Single-cell snapshot data can resolve a continuum of cellular states but do not uniquely determine the dynamics governing transitions between them. Howe