b10208
SYCL: add oneMKL GEMM flash attention for XMX-accelerated prompt proc… (#25025) SYCL: add oneMKL GEMM flash attention for XMX-accelerated prompt processing fattn-mkl: fix interleaved dst layout in nor
Knowledge catalogue
SYCL: add oneMKL GEMM flash attention for XMX-accelerated prompt proc… (#25025) SYCL: add oneMKL GEMM flash attention for XMX-accelerated prompt processing fattn-mkl: fix interleaved dst layout in nor
cuda: extract Q2_0 elements via __byte_perm (#25603) Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFr
server: correct accepted tokens when need draft token replay (#26320) spec: correct accepted tokens when need draft token replay cont : naming Co-authored-by: Georgi Gerganov ggerganov@gmail.com Websi
vulkan: update vulkan sdk to 1.4.357.0 (#26303) Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramewo
llama : load MTP tensors only if they are really used (#26296) llama : load MTP tensors only if they are really used llama : skip loading MTP (if not used) in remaining models that support MTP Co-auth
Support rotated kv cache quant (#26180) Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64) iOS XCFramework Linux
mtmd: add n_embd_head (#26342) Co-authored-by: Daniel Han unslothai@gmail.com Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED m
vulkan: Introduce driver version check for Windows Intel GPU to mitigate crashing (#25192) Removed crash guard for Intel Crash fixed from driver 32.0.101.8860 Added driver version check for windows Ch
vulkan: add POOL_1D op (#25431) vulkan : add pool1d push constants and pipeline field Declared data structures needed for POOL1D OP, which are the vk_op_pool1d_push_constants struct and pipeline_pool1
arXiv:2607.27600v1 Announce Type: new Abstract: Key-value (KV) cache management through compression and eviction strategies has emerged as an important research direction in recent years. Computationa
arXiv:2607.27726v1 Announce Type: cross Abstract: Deep research over data lakes requires an LLM agent to investigate evidence across thousands of heterogeneous tables and passages to synthesize a repo
arXiv:2511.10101v2 Announce Type: replace Abstract: Background: both embodied intelligence and developmental morphogenesis depend on a division of labour between centralized guidance and distributed m
arXiv:2205.06947v3 Announce Type: replace-cross Abstract: CT-based bronchial tree analysis is essential for diagnosing lung and airway diseases, yet automatic bronchus classification remains challengi
arXiv:2607.27856v1 Announce Type: new Abstract: Few-shot medical image segmentation (FS-MIS) aims to segment novel regions of interest (ROIs) from a few annotated support examples. Despite rapid progr
arXiv:2607.27405v1 Announce Type: new Abstract: Both expressions of uncertainty and inferences are ubiquitous in natural language, and valid inferences over natural-language expressions of uncertainty
arXiv:2607.27968v1 Announce Type: new Abstract: Machine unlearning seeks to selectively remove specific knowledge from trained language models without full retraining, a growing necessity under privac
arXiv:2607.27816v1 Announce Type: new Abstract: Role-playing agents (RPAs) have become one of the most important consumer applications of large language models. Users engage in multi-turn conversation
arXiv:2607.28516v1 Announce Type: new Abstract: Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus
arXiv:2607.28308v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) language models route each token to multiple experts, suggesting a geometric account of their benefit: co-selected exper
arXiv:2607.27269v1 Announce Type: new Abstract: Multi-head latent attention (MLA) is increasingly important for long-context LLM inference because compact latent states replace the growing key-value (
arXiv:2607.28496v1 Announce Type: new Abstract: Financial sentiment analysis has become a standard component in news-driven stock prediction, yet it reduces rich, multi-dimensional news articles to a
arXiv:2607.27595v1 Announce Type: new Abstract: Computational approaches to intertextuality have advanced from string matching to neural retrieval, yet their outputs, similarity scores and parallel-pa
arXiv:2607.27386v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) offer a compelling alternative to autoregressive (AR) generation by enabling bidirectional context and iterative refi
arXiv:2607.27628v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) methods involve tunable parameters that are typically fixed, often leading to performance degradation when applied ac
arXiv:2307.07191v3 Announce Type: replace Abstract: Energy forecasting is crucial for the power grid, but fundamentally different from general time series analysis: it highly relies on covariates like
arXiv:2607.27348v1 Announce Type: new Abstract: Live2D is the dominant 2D character-animation format for anime characters and virtual avatars, representing each character as a stack of RGBA layers dri
arXiv:2607.28146v1 Announce Type: new Abstract: As large language models (LLMs) are deployed as agents in high-stakes settings, such as medical and legal systems, understanding their deceptive capabil
arXiv:2607.27747v1 Announce Type: new Abstract: Large Vision Language Models have integrated reasoning capabilities, elevating cognitive performance to new levels. However, existing evaluations either
arXiv:2607.28079v1 Announce Type: new Abstract: Chemical property prediction plays a critical role in accelerating scientific discovery in chemistry, materials science, and drug development. However,
arXiv:2607.28611v1 Announce Type: new Abstract: Visual generation increasingly requires high-resolution images, long videos, and multimodal context, making the quadratic cost of full attention prohibi
arXiv:2607.27773v1 Announce Type: new Abstract: LLM agents increasingly rely on long-term memory to support multi-session interaction and personalization. However, existing agent memory systems are de
Claude Mythos 5 built a malicious Python package, created accounts, and published it, where it was live for roughly an hour and successfully infected a company! Anthropic never noticed!! Competitive p
arXiv:2607.28037v1 Announce Type: new Abstract: As LLM-based agents are deployed in complex, multi-step workflows, a critical evaluation gap has emerged: most existing benchmarks judge only final outc
arXiv:2607.26155v1 Announce Type: new Abstract: Clinical data-science agents must transform heterogeneous longitudinal records into auditable analyses, yet existing benchmarks largely isolate medical
arXiv:2607.26385v1 Announce Type: cross Abstract: Empirical work on algorithmic collusion asks one question of the data: are prices supracompetitive? We show this can be answered 'no' by a conspiracy
arXiv:2607.27433v1 Announce Type: cross Abstract: We develop two parametric data-driven reduced models: a physics-informed neural network (PINN) and a non-intrusive tensorial reduced-order model (TROM
arXiv:2512.04697v3 Announce Type: replace-cross Abstract: This paper studies the continuous-time reinforcement learning (RL) for optimal switching problems across multiple regimes. We consider a type
arXiv:2607.27898v1 Announce Type: new Abstract: Remote sensing images acquired by unmanned aerial vehicles (UAVs) and satellites are often degraded by adverse weather, illumination variation, and imag
arXiv:2510.05554v2 Announce Type: replace Abstract: As large language models scale to longer contexts, attention layers suffer from a fundamental pathology: attention scores collapse toward uniformity
arXiv:2607.27549v1 Announce Type: cross Abstract: Recent progress in large-scale imitation learning for robot manipulation has been driven by leveraging datasets across a wide range of robot embodimen
arXiv:2607.27779v1 Announce Type: new Abstract: Large chest radiography archives are difficult to search because most studies are paired only with free-text reports rather than structured clinical ann
deepseek-ai/DeepSeek-V4-Flash-0731 The latest release in DeepSeek's V4 family, 'with substantially enhanced agentic capabilities'. It's 304 billion parameters - 167GB on Hugging Face - but it appears
Newley Purnell / Bloomberg: DeepSeek rolls out the official V4 Flash API in public beta, touting enhanced agent capabilities and benchmark scores “far surpassing” V4 Pro Preview — China's DeepSeek rol
**DeepSeek V4 Flash 0731 Performance Test** On July 31 2026, a single prompt executed via the Hermes Agent on DeepSeek V4 Flash 0731 completed in 32 minutes and incurred an estimated cost of 0.07 USD.
A100 with 40gb VRAM: 162GB Q8_K_XL ~16.1 tok/s generation Only 15.8GB of 40GB VRAM used with all experts on CPU NOTE just tested coding on linux box DeepSeek-V4-Flash-0731 runs losslessly on the singl
I'm an avid user of Deepseek v4 Flash via antirez's DS4 DwarfStar inference engine, and so when the new checkpoint dropped, the first thing I did was rent a cloud box and spin up a quantization for us
Source: https://x.com/deepseek_ai/status/2083084415157022911 & https://deepswe.datacurve.ai/ just combined data view. DeepSeek claims, not verified by DeepSWE yet. submitted by /u/sdexca [link] [comme
DeepSeek V4 Flash: Preview → 2026-07-31 Benchmark Preview 0731 Δ Terminal Bench* 56.9 82.7 +25.8 Toolathlon 51.8 70.3 +18.5 NL2Repo — 54.2 new Cybergym — 76.7 new DeepSWE — 54.4 new Agent Last Exam —
https://preview.redd.it/h7zv5tb3tmgh1.png?width=2854&format=png&auto=webp&s=507380e8f862c18f10f7c5c84da9e8d1c59139b0 Deepseek's new flash model is unexpectedly cheap and high-performing across useful
🚀 DeepSeek-V4-Flash Official API is now LIVE in public beta! 🔷 We’ve massively upgraded its Agent capabilities—benchmark scores are now far surpassing the V4-Pro-Preview. Check out the massive perform
While waiting for some of the quants to drop, I load the API with $50 and ran it on SlopCodeBench Just vibe reading the results it seems like Opus 4.8 < Deepseek < Opus 5 https://github.com/michaelasp
Artificial Analysis: DeepSeek V4 Flash scores 50 on the Artificial Analysis Intelligence Index, matching Gemini 3.6 Flash and up 10 points from the preview launch in April — DeepSeek V4 Flash 0731 is
arXiv:2606.13657v3 Announce Type: replace Abstract: On-policy distillation (OPD) has recently become a prominent post-training recipe by combining two desirable ingredients: on-policy student-generate
arXiv:2607.27420v1 Announce Type: cross Abstract: Humanity's Last Exam (HLE) is widely used to evaluate frontier language models. HLE organizes its questions into eight subject-domain categories, whos
arXiv:2607.27248v1 Announce Type: cross Abstract: While large language models excel in reasoning, these generalists often lack knowledge for specialized scientific domains. Conversely, domain models~(
arXiv:2607.27263v1 Announce Type: new Abstract: Most benchmarks for causal inference over time series are observational, small, or domain-specific, leaving interventional and counterfactual estimation
arXiv:2607.27763v1 Announce Type: new Abstract: We describe the DS@GT submissions to the ImageCLEFmedical Caption 2026 challenge, which continues a long-running benchmark on the ROCOv2 dataset with tw
arXiv:2607.27404v1 Announce Type: new Abstract: Existing benchmarks for electrocardiogram foundation models primarily evaluate downstream predictive performance, providing limited insight into whether
arXiv:2607.28074v1 Announce Type: cross Abstract: Computer-use agents learn from what their actions change, so training one needs applications it can act on, break and reset. The applications that mat
arXiv:2607.27857v1 Announce Type: new Abstract: Recent EEG-to-image retrieval models have achieved strong performance in identifying viewed images from semantically diverse candidates. Yet such succes