Knowledge catalogue
Perplexity AI Inc. today introduced a new feature that takes its current agentic artificial intelligence service, Computer, to perform better with greater security. The company introduced SPACE, a san
arXiv:2607.12111v1 Announce Type: cross Abstract: Agentic AI systems are reshaping communications and networking by deploying autonomous intelligent agents capable of collaborative learning while main
arXiv:2607.12726v1 Announce Type: cross Abstract: Global fits in high energy physics and cosmology often face the challenge of exploring high-dimensional parameter spaces with computationally expensiv
arXiv:2607.09760v2 Announce Type: replace-cross Abstract: Radio frequency fingerprint identification (RFFI) exploits transmitter-specific hardware imperfections as physicallayer identity cues for Inte
arXiv:2607.12385v1 Announce Type: new Abstract: A significant challenge in agentic AI is prospective memory: the ability to execute an intention at a specific future cue or state while other activitie
arXiv:2601.11443v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has emerged as a powerful approach for enhancing large language models' question-answering capabilities through
arXiv:2607.11327v2 Announce Type: replace-cross Abstract: Model editing keeps large language models (LLMs) up to date without retraining, but temporal facts expose a limitation of the prevailing locat
arXiv:2607.12269v1 Announce Type: new Abstract: We introduce Quantum Port-Hamiltonian Neural Networks (Q-pHNNs), a family of parameterised quantum circuits that learn classical dynamics in a structure
arXiv:2505.12682v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly released under restricted licenses, creating a growing need for robust model ownership verification. E
arXiv:2607.12903v1 Announce Type: new Abstract: In operational 1:N face identification, a crucial question arises for each probe: is this person enrolled in the gallery or not? The stakes are high and
arXiv:2607.12216v1 Announce Type: cross Abstract: Multi-agent and memory-augmented LLM systems often place coordination content, shared state, prior discussion, tool outputs, summaries, and role instr
Frontier models are just so good though. Fable 5... Gemini 3.1 Pro for design critique and brainstorming. Grok for verification passes. Antigravity with Gemini 3.5 Flash for rote plan execution. Openc
arXiv:2607.12909v1 Announce Type: cross Abstract: Falling detection is vital for elderly care and intelligent surveillance; however, prevailing vision-based approaches predominantly frame it as static
arXiv:2607.12495v1 Announce Type: new Abstract: Creating photorealistic 3D assets requires bridging the appearance gap between real-world observations and synthetic models. A promising approach is to
Some fixes & boost(pp) for SYCL/Intel. Merged PRs: [SYCL] Flash Attention with XMX engine via oneDNN graph API (SDPA) on KV f16 for Xe2 ; Qwen3.6-27b-Q8_0 prefill speed up x1.21 at p=512 and x4.26 at
arXiv:2607.10541v2 Announce Type: replace-cross Abstract: Sequential recommender systems typically infer user preferences through single-pass encoding of interaction histories without iterative refine
arXiv:2607.12287v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models exhibit strong generalization for robotic manipulation, yet their high inference latency limits real time deployment
arXiv:2607.11928v1 Announce Type: new Abstract: Single-shot fringe projection profilometry (FPP) networks that regress depth directly can exploit a shape-prior shortcut, recovering depth from object b
arXiv:2607.12840v1 Announce Type: cross Abstract: Unconventional computing systems must demonstrate robust performance under real-world environmental conditions to enable practical deployments. We hav
arXiv:2607.12985v1 Announce Type: new Abstract: Aligned language models routinely misreport under non-evidential incentive pressure: they agree with a confident user or overstate certainty even when t
arXiv:2607.12227v1 Announce Type: new Abstract: We revisit the evaluation of automatic harness evolution for LLM agents. Existing harness evolution methods use unit test cases to search for harness co
arXiv:2512.04144v3 Announce Type: replace Abstract: Targeted interventions on language models, such as unlearning or model editing, aim to modify specific information, but their effects often propagat
arXiv:2503.06796v2 Announce Type: replace Abstract: Robot design is a complex and time-consuming process that requires specialized expertise. Gaining a deeper understanding of robot design data can en
arXiv:2607.12488v1 Announce Type: new Abstract: Molecular optimization in drug discovery, materials design, and catalysis requires searching vast chemical spaces under tight evaluation budgets, since
arXiv:2607.11950v1 Announce Type: cross Abstract: Brain field potentials are scale-free: their power spectra follow a 1/f^{eta} law whose aperiodic exponent eta tracks cortical state, and sleep depth
arXiv:2607.11889v1 Announce Type: cross Abstract: Large language models trained on unrestricted internet corpora inevitably embed information from the future, introducing lookahead bias that compromis
arXiv:2607.11970v1 Announce Type: cross Abstract: We develop an enhanced in-context learning (ICL) framework to improve the performance of pilot-based beamforming in multi-user multiple-input single-o
arXiv:2607.12477v1 Announce Type: new Abstract: Autonomous UAV systems increasingly rely on multimodal large language models (MLLMs) to operate in complex real-world environments. Such embodied scenar
arXiv:2607.11920v1 Announce Type: cross Abstract: Evaluating decisions made under uncertainty is hard when labeled outcomes are scarce, costly, or confounded with luck. We treat subjective expected ut
arXiv:2607.11910v1 Announce Type: cross Abstract: Optimizing composite stacking sequences to match continuous targets (e.g., Lamination or Buckling Parameters) with discrete manufacturing constraints
arXiv:2506.12339v2 Announce Type: replace-cross Abstract: We present SheetMind, a modular multi-agent framework powered by large language models (LLMs) for spreadsheet automation via natural language
arXiv:2607.12792v1 Announce Type: cross Abstract: Jailbreak-robustness research typically evaluates safety through generated responses using an LLM-as-judge approach. Such evaluations, however, are se
arXiv:2607.11624v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) algorithms classically suffer from poor sample efficiency. In robotics, a recent line of work has emerged addressi
arXiv:2607.11890v1 Announce Type: cross Abstract: Open-ended surveys offer valuable insights, but they are notoriously difficult to analyze at scale. Building on previous work that employed traditiona
someone just told me about this take* on CUA this is one of those gell mann moments for me lol. i've been watching computer use since World of Bits (Shi, fan, karpathy, hernandez & liang 2017). we wer
Something I have been thinking about: in the past, the best engineers I knew spent a lot of time automating their work in various ways. Better vim/emacs automations, writing lint rules to catch repeat
Cybersecurity firm Sophos Ltd. today launched Sophos Fusion, a single platform that ties together its security operations, endpoint, network, identity, email and cloud protection. Sophos calls it the
arXiv:2603.08503v2 Announce Type: replace Abstract: Omnidirectional images are increasingly used in robotics and vision due to their wide field of view. However, extending 3D Gaussian Splatting (3DGS)
arXiv:2602.12783v3 Announce Type: replace-cross Abstract: Spoken query retrieval is an important interaction mode in modern information retrieval. However, existing evaluation datasets are often limit
Introduction RxBrain (Hy-Embodied-RxBrain-1.0) is a unified multimodal foundation model for embodied cognition — a single model that couples language reasoning with visual imagination to deliver three
arXiv:2607.12497v1 Announce Type: new Abstract: Beyond perception, reasoning is essential in remote sensing for advanced interpretation, inference, and decision-making. Recent advances in large langua
arXiv:2607.13028v1 Announce Type: cross Abstract: Training robust autonomous driving agents requires a simulator that is fast enough for reinforcement learning at scale, realistic enough to ground beh
arXiv:2607.12208v1 Announce Type: cross Abstract: We show that the Benjamini--Hochberg procedure can fail to control the false discovery rate (FDR) at its nominal level for correlated two-sided Gaussi
The Blender MCP is now part of the Hermes Agent MCP Catalog! Easily activate and install the Blender MCP by running `hermes mcp install blender` and ask your agent to start using blender. Hermes will
arXiv:2607.12079v1 Announce Type: new Abstract: Decoding continuous language from fMRI signals remains a core challenge in non-invasive brain-computer interface research. We present two complementary
arXiv:2607.12963v1 Announce Type: new Abstract: As large language models (LLMs) grow more capable, they are increasingly deployed in context-rich settings where task inputs are often accompanied by lo
arXiv:2607.12796v1 Announce Type: cross Abstract: When a language model must pick one answer from a large space of equally valid options, which does it pick -- and how often is it the same answer ever
Written by: Corné de Jong Introduction Mandiant security assessments frequently identify publicly exposed serverless applications that lack authentication, often as a result of specific business requi
arXiv:2312.17670v5 Announce Type: replace Abstract: The Circle of Willis (CoW) is an important network of arteries connecting major circulations of the brain. Its vascular architecture is believed to
Thinking Machines just dropped a ~1T Omni model 🔥 > 1M context window, trained on 48T tokens of image, text, audio 🤯 > comes with a drafter, NVFP4 weights and Unsloth quants > transformers, llama.cpp
Thinky with a ~1T param, 41B active, apache-2 model Benchmarks are a clear step up from Nemotron Ultra (55B active), new best American model, and omni input. A bit behind GLM 5.2 on agentic benchies,
This is for pretraining based on nemotron nvp4 figures, mfu etc Large context, multimodal, long RL we are seeing now could make it a multiple of this Worth noting how good the lite model is, similar t
this was such a fun talk with Cat and Simon, hope you get to check it out if you missed it 🆕This Year In Claude https://www.youtube.com/watch?v=uU5Gv2h8-9g @simonw chats with @_catwu and @trq212 about
🆕This Year In Claude https://www.youtube.com/watch?v=uU5Gv2h8-9g @simonw chats with @_catwu and @trq212 about the state of: - @claudeai Code - Claude Fable - @anthropicai culture & product strategy -
arXiv:2607.12161v1 Announce Type: new Abstract: Context-reduction layers for API-based coding agents, including command-output compressors, retrieval rankers, and payload-optimizing proxies, are usual
arXiv:2607.11913v1 Announce Type: cross Abstract: Recent advancements in agentic AI have increasingly moved toward graph-based methods, driven by the demand for explainable, human-centered, and non-li
arXiv:2607.12480v1 Announce Type: new Abstract: This paper defines TRACE (Typed Reasoning And Commitment Evidence): a typed, versioned schema for recording reasoning traces, a reference procedure for
arXiv:2607.12267v1 Announce Type: cross Abstract: Language agents that interleave reasoning and tool use degrade sharply as reasoning chains lengthen, even when each individual step is easy. We trace
arXiv:2607.11933v1 Announce Type: new Abstract: Cross-encoders achieve high reranking accuracy in Retrieval-Augmented Generation (RAG) pipelines but impose quadratic inference costs that limit real-ti
Trending AND fastest-growing in the same month? Benchmarks change daily, but only @tryramp has the database of real receipts to track this. We can confirm: demand for open-weight inference and trainin