Knowledge catalogue
NVIDIA’s new GPUs in the Vera Rubin and Blackwell families set a new benchmark for agentic‑AI performance per watt on AgentX, an open‑source inference test that models realistic multi‑step, tool‑using
Chipmaker Nvidia Corp. says its dedicated artificial intelligence inference accelerator Groq 3 LPX has now entered full production as it strives to maintain its dominance in the world of AI compute. T
arXiv:2608.20932v1 Announce Type: new Abstract: Layout-to-image generation enables explicit spatial control through bounding-box layouts, yet bounding boxes specify only instance locations and cannot
arXiv:2608.21360v1 Announce Type: new Abstract: Recent omni-modal large language models (Omni-LLMs) show great potential as real-time video assistants, which continuously perceive environments and gui
arXiv:2608.21254v1 Announce Type: new Abstract: Accurate agricultural weed detection in real-world field conditions is essential for precision agriculture, enabling targeted intervention and reducing
arXiv:2409.16322v4 Announce Type: replace-cross Abstract: Alzheimer's Disease (AD) detection commonly employs machine learning classification models to distinguish between individuals with AD and thos
arXiv:2608.20640v1 Announce Type: cross Abstract: Multi-merchant e-commerce catalogs contain equivalent and related products under different merchant-scoped identifiers, fragmenting behavioral evidenc
An AQuA research loop let one LLM write an intraday trading feature and a second LLM review it for causality. The feature divided the volume seen so far by the day's final total volume. At prediction
arXiv:2410.08875v3 Announce Type: replace Abstract: Designing a network (e.g., a telecommunication or transport network) is mainly done offline, in a planning phase, prior to the operation of the netw
arXiv:2608.20856v1 Announce Type: new Abstract: Document-Level Relation Extraction (DocRE) relies heavily on costly manually annotated datasets, while large distant supervision resources such as DocRE
arXiv:2608.21224v1 Announce Type: new Abstract: Recently, there has been a great deal of research into improving AI methods and their application. The main focus is on tracking progress, enabling tran
arXiv:2608.20569v1 Announce Type: new Abstract: Are frontier models able to introspect about their internal states? Recent work suggests that under certain conditions a complex enough model can audit
Marcus Mendes / 9to5Mac: OpenAI restores 5-hour Codex and Work limits for ChatGPT Plus users, after weeks without the restriction, saying it would smoothen the load on its compute — Following several
arXiv:2603.28938v2 Announce Type: replace-cross Abstract: Optimism in the face of uncertainty is a popular approach to balance exploration and exploitation in reinforcement learning. Here, we consider
arXiv:2508.17488v4 Announce Type: replace Abstract: This paper tackles the critical challenge of optimizing multi-modality trackers by effectively adapting pre-trained models for RGB data. Existing fi
Our 2nd founder dinner in SF co-hosted by @jerryjliu0 and @GuangyuRobert at @Fundamental - the team behind @tryshortcutai Talking about existing moats in the AI era. Frontier labs are moving past mode
ToMoE: Converting Dense Large Language Models to Mixture-of-Experts through Dynamic Structural Pruning Large Language Models (LLMs) have demonstrated remarkable abilities in tackling a wide range of c
arXiv:2608.20438v1 Announce Type: cross Abstract: Population-level behavior in large-language-model (LLM) agents cannot be characterized by single-agent benchmarks. We introduce PV-SST, a peer-voted s
Perplexity has low tens of millions in revenue a month, and I’m not even talking about how much they lose. Nvidia had to step in to boost their valuation and give them first aid, either through cloud
arXiv:2510.09930v2 Announce Type: replace-cross Abstract: Real-world systems, ranging from industrial manufacturing to wearable healthcare, generate multivariate time series with hierarchical states r
arXiv:2608.21209v1 Announce Type: new Abstract: The rise of agentic AI enables LLMs to access diverse user data, raising critical privacy concerns. Prior work on contextual privacy studies whether LLM
arXiv:2608.21349v1 Announce Type: cross Abstract: Scarce data and tumor heterogeneity limit patient-level cancer treatment-response prediction. Existing approaches predict response from pretreatment m
arXiv:2603.01493v2 Announce Type: replace-cross Abstract: Personal photo albums are not merely collections of static images but living, ecological archives defined by temporal continuity, social entan
arXiv:2608.21031v1 Announce Type: new Abstract: We present PhysCaP, a Physics-Informed Code-as-Policy agent for active perception in robotic manipulation. While vision-language-action policies excel a
Physical artificial intelligence is emerging as the next major phase of AI. These systems not only generate content or analyze data but also perceive, reason about and act in the physical world. The o
TL;DR: I'm planning to spend around 100 on cloud GPUs to benchmark Qwen3.8-27B with a focus on questions that actually matter when running it locally: different quant levels/providers, 8-bit vs 16-bit
If you’re trying to run local LLMs on a normal laptop, an older desktop, integrated graphics, limited VRAM, or simply the hardware you already own, r/LowEndLocalAI is meant for you. The idea is simple
arXiv:2608.20626v1 Announce Type: cross Abstract: Soft, wearable robotic devices can deliver haptic feedback to support a wide range of tasks, such as extended reality, training various skills, and re
arXiv:2608.20387v1 Announce Type: cross Abstract: While recent text-to-speech (TTS) models achieve high naturalness, controlling fine-grained expression via natural-language instructions remains chall
arXiv:2608.20660v1 Announce Type: cross Abstract: Simulating a continuous-time quantum walk (CTQW) on a graph in the circuit model of quantum computing requires decomposing its Hamiltonian into terms
arXiv:2608.20825v1 Announce Type: new Abstract: Artificial intelligence systems increasingly make consequential judgments - which patient is deteriorating, which building is safe to enter, whether an
arXiv:2608.21359v1 Announce Type: cross Abstract: We develop a new direct accelerated Newton method for minimizing convex functions with Lipschitz continuous Hessian. The algorithm uses only primal va
arXiv:2608.20342v1 Announce Type: new Abstract: Large language model (LLM) coding agents start each session with an empty context window, discarding accumulated knowledge from prior work. We present P
arXiv:2608.20712v1 Announce Type: cross Abstract: We propose a novel object detection method that enables us to protect sensitive visual information of test images. Previous studies considering visual
arXiv:2608.20801v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have significantly advanced reranking in recommendation, effectively leveraging item-side information remains chall
arXiv:2608.21315v1 Announce Type: new Abstract: That a prompt's effect is not a property of the prompt is established: prompts optimised for one model degrade on another, and rankings reorder under ne
arXiv:2608.21074v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in research workflows and software development pipelines, yet their output remains sensitive to inp
arXiv:2608.20432v1 Announce Type: cross Abstract: Formal proofs in Lean 4 that pass the kernel's type checker can nonetheless vary widely in quality. We introduce ProofJudge, an agentic LLM-as-judge s
arXiv:2608.20638v1 Announce Type: cross Abstract: The edge-of-stability (EoS) phenomenon of Adam has been widely observed, while its underlying dynamical mechanism is not yet fully understood. We stud
arXiv:2608.20757v1 Announce Type: cross Abstract: We describe the PSK submission to the WMT 2026 Multilingual Instruction Shared Task. Our system uses the 3.35B-parameter Tiny Aya Global model with th
arXiv:2608.20953v1 Announce Type: cross Abstract: Serving large language models cheaply increasingly means shipping models that are both structurally compressed to a fraction of their parameters and q
arXiv:2507.19290v2 Announce Type: replace-cross Abstract: We study the problem of learning a structured approximation (low-rank, sparse, banded, etc.) to an unknown matrix A given access to matrix-vec
For the GPU poor among us: I'm curious what results you're getting with low quants of Qwen 27B 3.8. My main inference hardware is limited (Mac mini M4 24 GB), but I'm getting great results with Unslot
I ran the Aider benchmark on Qwen 3.8 27B FP8 with FP8 KV cache 256K context vLLM. The score: 72.9 This matches Gemini 2.5 Pro from 2025-04-12 which also scored 72.9. Beats Claude Opus 4 from 2025-05-
I commented on another Qwen 3.8 27B post that I was frustrated getting anything to work. You all gave some great comments. I nuked openwebui and straightened out my llama.cpp docker config. 1 hour of
Ornith does really well. TielCoder (https://llm-bench.io/benchmarks/cmt7kp2zj002r01lcmpchvlko) might be even a bit better in coding. Will give it a try soon. Details of the comparison see here: https:
With vision enabled I am able to run at 150k context on a single RTX 3090 and the results are just amazing. I was even able to write a gmail plugin for DeepSeek harness with locally hosted Qwen 3.8 27
I'm one of the co-authors of this paper. It's a seminal work in exploring the properties of 3D generated by LLMs via spatial programming. I've set up visual demonstrations of such 3D objects at: https
arXiv:2603.11252v2 Announce Type: replace Abstract: Although semantic 3D city models are internationally available and becoming increasingly detailed, the incorporation of material information remains
arXiv:2608.20845v1 Announce Type: new Abstract: Nearly every retrieval-augmented question-answering system in production ships with a hidden interpreter: on each query a language model re-derives the
arXiv:2509.09024v2 Announce Type: replace Abstract: The demand for lightweight and high-strength composite structures is rapidly growing in aerospace and robotics, particularly for optimized drone fra
arXiv:2608.21236v1 Announce Type: new Abstract: Representation engineering offers a lightweight means of controlling language-model behavior by modifying intermediate hidden states, but its direct app
arXiv:2608.20870v1 Announce Type: new Abstract: Infrared small target detection is still challenging in remote sensing imagery, because the targets are extremely small, exhibit weak local contrast, an
arXiv:2608.21305v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has demonstrated significant gains in image captioning, yet it is still limited in encouraging Large Vision-Language Model
Thanks to Unsloth Dynamic 3.0 quants coming in slightly leaner and better preserved, I settled on Qwen 3.8 27B (`UD_Q4_K_XL`) at 100K context as my daily driver for Hermes Agent and OpenCode. On an RT
arXiv:2604.01479v3 Announce Type: replace Abstract: Sparse-view 3D modeling represents a fundamental tension between reconstruction fidelity and generative plausibility. While feed-forward reconstruct
arXiv:2608.21022v1 Announce Type: new Abstract: Micro-actions are subtle, short, low-amplitude body movements, such as a fidgeting hand or a slight head tilt, that humans perform with little conscious
arXiv:2504.13988v2 Announce Type: replace Abstract: This work defends the 'Whole Hog Thesis': sophisticated Large Language Models (LLMs) like ChatGPT are full-blown linguistic and cognitive agents, po
arXiv:2608.20621v1 Announce Type: new Abstract: Text-guided zero-shot object counters excel at spatial localization but categorize poorly on novel or fine-grained classes: natural language is too coar
arXiv:2608.20869v1 Announce Type: new Abstract: Predicting transition states (TS) in chemical reactions is crucial, as they provide insights into reaction mechanisms. Recent work on TS prediction have