Knowledge catalogue
Yael Grauer / The Verge: Anthropic and other researchers detail how thousands of people were catfished by dating scam apps using LLM-generated replies from Claude and other models — Security researche
Days after Anthropic PBC Chief Executive Dario Amodei rocked the artificial intelligence world by calling on leading model makers to coordinate on the slowdown on the pace of development, the company
Anthropic: Anthropic outlines metrics to track AI development at frontier labs: how much AI R&D is done by AI, how well agents are overseen, and how compute is allocated — AI systems are becoming expo
Claude: Anthropic redesigns Claude projects, letting users describe work in one conversation and have Claude manage it across parallel threads, starting in Claude Code — A new experience for Claude pr
Shirin Ghaffary / Bloomberg: Anthropic says Claude “leads” 26% of its AI R&D work, up from 1% in March, and “collaborates” on 90%+, doing large chunks of work under close human direction — More than a
arXiv:2609.18219v1 Announce Type: cross Abstract: Quantum Reinforcement Learning (QRL) represents policies as variational quantum circuits (VQCs), making it attractive for combinatorial optimization s
arXiv:2609.18169v1 Announce Type: new Abstract: Self-motion manifold (SMM) characterizes the geometric structure of the infinite inverse kinematic solutions set of a redundant manipulator at a fixed e
arXiv:2604.08194v2 Announce Type: replace Abstract: The Maxey-Riley-Gatignol equations (MaRGE) model the motion of spherical inertial particles in a fluid. They contain the Basset force, an integral t
Basically the title. Training models take time and if a model was already in the process of pre-training/RL then it can't be re-cooked with any new architectural improvement that has been discovered i
arXiv:2609.18849v1 Announce Type: cross Abstract: An agentic request spends substantial wall-clock time waiting for tools, and its KV cache holds GPU memory the whole time. Serving systems decide whet
arXiv:2609.18864v1 Announce Type: cross Abstract: Privacy evaluations of tool-using LLM agents often inspect a designated action, final response, or attacker report. These local proxies can miss unaut
arXiv:2609.17943v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by attention, whose repeated KV-cache reads make decoding memory-bound. Self-speculative decoding alleviate
Astra for Law: Frontier intelligence built for your practice. A new offering powered by GPT-6 Astra with tools, settings, and context to support the expertise and judgment of lawyers and legal technol
Astra for Law will initially be offered to selected firms through Trusted Access in ChatGPT and Codex, with API access coming soon. We’ll maintain the legal configuration so builders can focus on thei
arXiv:2609.18813v1 Announce Type: new Abstract: Multi-robot task and motion planning (MR-TAMP) requires jointly reasoning about discrete task decisions and continuous collision-free motions of multipl
arXiv:2609.18320v1 Announce Type: new Abstract: Large Language Models (LLMs) frequently exhibit hallucinations, presenting a major barrier to reliability in complex reasoning tasks. While traditional
arXiv:2609.17923v1 Announce Type: new Abstract: Sports highlight detection aims to identify the most exciting and meaningful moments from long sports videos. While existing methods often emphasize vis
arXiv:2609.18952v1 Announce Type: cross Abstract: Early detection of dental caries remains challenging due to limitations in traditional diagnostic methods, particularly for proximal lesions in poster
arXiv:2609.18338v1 Announce Type: cross Abstract: Adaptive security at the network edge increasingly relies on automated planners, including rule-based controllers, learned policies, and LLM-assisted
arXiv:2609.18123v1 Announce Type: new Abstract: Large language model agents tune GPU kernels and serving engines through a closed loop of propose, measure, and keep, but the measurements behind this l
vulkan: work around NV bug with argsort_large.comp (#28975) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48059150 macOS/iOS: macOS Apple Silicon (arm64)
[SYCL] Fix function signature for ggml_backend_sycl_split_buffer_type (#28981) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48082811 macOS/iOS: macOS App
vulkan: support qwen4exp hc ops (#28988) vulkan: support qwen4exp hc ops fix stale comment [no-ci] Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48109146
vulkan: fix buffer_reference alignment in im2col shaders (#28996) Both im2col.comp and im2col_3d.comp declare D_ptr without an explicit buffer_reference_align, so glslang emits writes through it as Al
opencl: fix various warnings (#28984) opencl: fix warnings opencl: fix warnings for non adreno Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48132480 macO
sycl: ssm_conv: fuse the SiLU epilogue into the ssm_conv kernel (#28929) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48138242 macOS/iOS: macOS Apple Sil
vulkan: skip unneeded MoE work in mul_mm coopmat1 path (#25483) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48144237 macOS/iOS: macOS Apple Silicon (arm
sycl : fix the B70 mem allocate error when >19.3GB (#28953) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48150237 macOS/iOS: macOS Apple Silicon (arm64)
gguf : align the data section relative to the GGUF start, not the file (#28993) gguf : align the data section relative to the GGUF start, not the file gguf_init_from_file_ptr reads a GGUF from the cur
chat : add message delimiters to the DeepSeek V3.2/V4 parser (#29008) chat : add message delimiters to the DeepSeek V3.2/V4 parser Assisted-by: Claude Co-authored-by: Sigbjørn Skjæret sigbjorn.skjaere
vulkan: split buffers and debug code into separate files, add shared headers (#28732) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48170206 macOS/iOS: ma
openvino : Update OpenVINO to 2026.4;fix clangd,MSVC warnings; (#29009) Update to openvino-2026.4 Update OV docs ggml-openvino : fix clangd and MSVC warnings fix int to ptr cast, more internal linkage
model : extend Nemotron MTP support (#29018) first fix removed unnecessary declarations Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48188464 macOS/iOS:
model : skip gate_up_exps if TENSOR_SKIP is set (#29014) required for qwen35moe if MTP tensors are fused but not loaded Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/a
rpc : skip ACCEL devices (#29020) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48232585 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64
ci : add missing evict-old-files (#29041) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/48252257 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silico
arXiv:2609.18366v1 Announce Type: new Abstract: Reliable agent evaluation is complicated by automatic harness optimization, which repeatedly uses a released benchmark B_{rel} to guide a Proposer that
arXiv:2609.18965v1 Announce Type: cross Abstract: This paper presents BadQubits, an LLM-based framework for static pre-execution detection of structurally harmful OpenQASM 2.0 circuits. The framework
Banger release from NVIDIA. They just published a report on NeMo Data Designer, their open-source synthetic data tool. It's a declarative config which makes a synthetic data pipeline easy to review, s
arXiv:2602.16218v2 Announce Type: replace Abstract: Bayesian quadrature is a probabilistic, model-based approach to numerical integration, the estimation of intractable integrals, or expectations. Alt
Hey everyone! I'm a beginner getting into local LLMs, and so far I'm familiar with Ollama. I've used it to download and run models locally, but I'm starting to see a lot of other tools being mentioned
arXiv:2609.18203v1 Announce Type: new Abstract: Human values are deep motivational orientations that shape human behaviors. In e-commerce, they reveal the stable drivers behind users' purchase decisio
arXiv:2609.18273v1 Announce Type: new Abstract: Web browsing often appears ephemeral: users visit a few websites, complete a task, and move on. However, even short fragments of browsing activity can c
arXiv:2609.18270v1 Announce Type: new Abstract: Payment operations are a critical financial infrastructure, but the value of large language models in this domain remains unclear because payment rules
arXiv:2609.19071v1 Announce Type: new Abstract: Extracting SNP-phenotype associations from biomedical literature is vital but challenging. We benchmarked diverse NLP models, including MLMs, hybrid arc
arXiv:2609.18130v1 Announce Type: cross Abstract: Surrogate-assisted evolutionary algorithms (SAEAs) are effective methods for solving expensive optimization problems (EOPs), where surrogate models re
arXiv:2609.18628v1 Announce Type: new Abstract: Visual-inertial odometry (VIO) is a core capability for autonomous operation in GPS-denied subterranean environments, yet its reliability can degrade sh
Been outta AI space for the last month , whats a good current finetune or comfig for MiniMax , turbo lora etc a workflow would be aprecciated , gonna check civitai later aswell submitted by /u/tricck3
https://www.curseforge.com/minecraft/mc-mods/verity-je Hi guys <3 What is the best performing ai agent that works with this mod? its called the verity mod. to be more general for anyone who doesnt kno
arXiv:2609.18204v1 Announce Type: cross Abstract: Organizations increasingly use oversight loops where one large language model (LLM) audits another's outputs alongside procedural traces of claimed st
arXiv:2609.18173v1 Announce Type: cross Abstract: Vehicle tracking is fundamental to applications ranging from urban mobility and public safety to security and defense. Conventional tracking relies on
arXiv:2609.18673v1 Announce Type: cross Abstract: Speaker de-identification (SDID) aims to preserve privacy by concealing speaker identity while maintaining speech utility. However, current evaluation
arXiv:2609.18078v1 Announce Type: new Abstract: Warm-start transfer can make algorithmic tasks generalize rapidly, yet it is unclear which model components provide the gain and whether that gain remai
arXiv:2609.18804v1 Announce Type: new Abstract: Identifying technological trends is a core scientometric task, yet traditional frequency-based approaches struggle to capture substantial meaning shifts
arXiv:2609.18909v1 Announce Type: cross Abstract: Agent benchmarks are substantially more costly to evaluate than conventional LLM benchmarks. Benchmark compression is therefore a natural solution, ye
arXiv:2609.17753v1 Announce Type: new Abstract: Reference labels used to train medical image classification models are not always as certain as they may appear, and this uncertainty has implications o
arXiv:2609.18100v1 Announce Type: cross Abstract: Synthetic data can reduce the cost of collecting and annotating training data for robotic perception, but generating sensor observations that preserve
arXiv:2609.18314v1 Announce Type: new Abstract: Loss spikes are recurrent instabilities in neural-network training and can arise from multiple mechanisms. For Adam in particular, macroscopic loss spik
arXiv:2609.18488v1 Announce Type: cross Abstract: Diffusion and flow-matching models are typically trained by corrupting data through independently sampled Gaussian noise. While simple and scalable, t
arXiv:2609.18515v1 Announce Type: new Abstract: Safety alignment teaches large language models (LLMs) to recognize harmful requests and reject risky instructions. Yet aligned models can fail when harm