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Aristotle said 'we should not think human things because we are human, nor mortal things because we are mortal' we should strive to live as though we are more - to 'immortalize' and live according to

arXiv:2604.04087v2 Announce Type: replace Abstract: We introduce ArrowFlow, a machine learning architecture that operates entirely in the space of permutations. Its computational units are ranking fil

This week we've got tandem hands-ons with Google's new Gemini AI agent - Spark - from my colleagues David Pierce and Jay Peters. Their takeaways are similar: It's so effective that it's scary. Spark k

As your application evolves with new features, you should periodically re-run SEO scans to ensure optimal search engine visibility and track your app's traffic metrics to monitor performance and user

arXiv:2501.17377v4 Announce Type: replace-cross Abstract: Deep Reinforcement Learning (DRL) has emerged as a promising approach for solving Combinatorial Optimization (CO) problems, such as the 3D Bin

arXiv:2606.03175v1 Announce Type: new Abstract: Instance Goal Navigation (IGN) requires an embodied agent to find a specific object instance among distractors from an underspecified natural-language d

arXiv:2605.11954v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in social science as scalable measurement tools for converting unstructured text into variables t

arXiv:2604.01410v2 Announce Type: replace Abstract: Text production (and translations) proceeds in the form of stretches of typing, interrupted by keystroke pauses. It is often assumed that fast typin

arXiv:2606.02598v1 Announce Type: new Abstract: Accurate and generalizable estimation of cognitive workload from electroencephalography (EEG) is critical for human-centered and safety-critical systems

arXiv:2507.21638v2 Announce Type: replace Abstract: The development of reinforcement learning (RL) algorithms has been largely driven by ambitious challenge tasks and benchmarks. Games have dominated

arXiv:2606.03070v1 Announce Type: cross Abstract: Asynchronous reinforcement learning can improve language-model post-training throughput by decoupling response generation from policy optimization, bu

At @harvey, the engineering team integrated Spectre — their internal background agent — into Devin Desktop. Now Spectre's organizational context can live on every engineer's laptop and flow across the

At this point, I suspect you could put endpoints named 0pus 4.8 & GPT 5.S in your apps powered by open-source models and it would get massive usage without people complaining. The power of 'frontier'

arXiv:2606.02924v1 Announce Type: new Abstract: Autonomous driving perception is typically evaluated on clean benchmark data, yet real-world deployment requires robustness to rare, structured, and pot

arXiv:2606.03540v1 Announce Type: new Abstract: Existing human attention (saliency) modeling methods persist as highly fragmented across modalities, scenes, and task formulations. Consequently, even w

arXiv:2606.02737v1 Announce Type: cross Abstract: Dense retrieval models exhibit positional bias: retrieval effectiveness degrades when relevant information appears later in a passage (Zeng et al., 20

arXiv:2604.06052v2 Announce Type: replace Abstract: Text-to-image diffusion models exhibit remarkable generative capabilities, yet their internal operations remain opaque, particularly when handling p

arXiv:2606.03885v1 Announce Type: new Abstract: Feature attribution methods explain predictions by assigning importance scores to input features. Path-based methods such as Integrated Gradients are es

arXiv:2606.02604v1 Announce Type: cross Abstract: ESG and climate risk data remain fragmented across heterogeneous Scope 1, Scope 2, and Scope 3 reporting environments, while conventional validation p

arXiv:2606.03031v1 Announce Type: new Abstract: Structured financial audit verification is difficult for language-model agents because correctness depends on structured evidence rather than text alone

arXiv:2606.03173v1 Announce Type: cross Abstract: The rise of `kidfluencers' on YouTube has raised ethical concerns about child digital labor and exploitation. While emerging legislation attempts to r

arXiv:2606.03347v1 Announce Type: cross Abstract: Score-based diffusion models have emerged as prominent deep generative models; however, their application to tabular data remains challenging because

arXiv:2606.03664v1 Announce Type: cross Abstract: Ultra Reliable and Low Latency Communications (URLLC) was one of the main motivations behind 5G, with 3GPP advertising 1-10 ms latency targets for app

arXiv:2606.02775v1 Announce Type: new Abstract: The KV-cache is the right memory for datacenters but the wrong memory for robots. Datacenter inference batches many short requests and resets them, amor

arXiv:2511.02304v2 Announce Type: replace-cross Abstract: We study learning multi-task, multi-agent policies for cooperative, temporal objectives, under centralized training, decentralized execution.

arXiv:2606.02809v1 Announce Type: new Abstract: Evaluating vision-language models (VLMs) on medical images requires benchmarks that are clinically grounded, scalable, and controlled for evaluation con

arXiv:2606.03340v1 Announce Type: new Abstract: Libraries require autonomous robots to move quietly through narrow aisles while remaining safe around readers, chairs, bags, and carts. This paper prese

arXiv:2606.03576v1 Announce Type: new Abstract: Scholarly text classification supports literature organization, subject indexing, and research intelligence, but Chinese scholarly corpora often contain

arXiv:2606.03506v1 Announce Type: new Abstract: Existing 3D avatar outfit transfer methods face distinct challenges: approaches that lift 2D edits to 3D often suffer from outfit or identity quality de

arXiv:2606.02724v1 Announce Type: cross Abstract: Audio-visual speaker tracking aims to localize and track active speakers by leveraging auditory and visual cues, enabling fine-grained, human-centric

The search results show general llama.cpp information and references to other recent builds (like b9484), but the specific details for b9487 were not clearly accessible. Based on the context from llam

Release b9488 of llama.cpp was published on June 3, 2026 , and includes support for Qwen3 SSM architectures with additions like LLM_KV_ATTENTION_RECURRENT_LAYERS . The release also fixes a bug in comm

Release b9489 of llama.cpp includes updates to hidden_act mapping in llama-model.cpp, additions of granite embedding multilingual R2 models, and support for setting hidden_activation in GGUF files. Th

b9491 is a release of llama.cpp , a C/C++ implementation of large language model inference that enables running LLMs locally with minimal dependencies. This release likely contains bug fixes, feature

B9493 is a release of llama.cpp, an LLM inference framework in C/C++ . This release includes updates to model support, such as centralized hidden activation mappings and additions for granite embeddin

The search results do not contain specific details about the b9494 release. Based on the context from the llama.cpp GitHub releases page, b9494 is an intermediate build release of llama.cpp, a C/C++ p

The search didn't return specific information about release b9495. Based on the available information about llama.cpp releases, here's a summary: llama.cpp enables LLM inference with minimal setup and

The search results do not contain specific information about release b9496. Based on the available context, b9496 is a build/release version of llama.cpp, a C/C++ implementation for efficient LLM infe

arXiv:2606.03287v1 Announce Type: new Abstract: Feed-forward models for 3D reconstruction have achieved strong performance using deep cross-view attention to exchange information across images. Howeve

arXiv:2606.03785v1 Announce Type: new Abstract: Backdoor attacks in Large Language Models (LLMs) are a growing security concern, where models can generate adversary-chosen content. Existing defenses t

arXiv:2606.03091v1 Announce Type: cross Abstract: Sequential recommendation systems are widely adopted but often deployed as black-box APIs, which has driven recent interest in model extraction to rep

arXiv:2602.18084v2 Announce Type: replace Abstract: Equivariance is central to graph generative models, as it ensures the model respects the permutation symmetry of graphs. However, strict equivarianc

arXiv:2606.03504v1 Announce Type: cross Abstract: We present BaltiVoice, a 16.8-hour read-speech corpus for Balti (ISO 639-3: bft), a Tibetic language spoken in Gilgit-Baltistan, Pakistan, with no pri

arXiv:2606.03212v1 Announce Type: new Abstract: Low-rank tensor decomposition (TD) is usually effective on clean, fully observed data, but it often degrades under severe missingness or noise. Low-rank

Common bean plants detect molecules in caterpillar saliva and release a scent that attracts predatory wasps using a single immune receptor called INR (inceptin receptor). This receptor recognizes ince

arXiv:2606.02937v1 Announce Type: cross Abstract: Multi-view video recordings are increasingly used to capture the 3D movements of animals in experimental settings, yet extracting rich 3D representati