DeepSeek v4 Flash has a nice bump in Capability
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 —
Knowledge catalogue
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:2607.27784v1 Announce Type: new Abstract: Scalable collection of dexterous manipulation demonstrations remains a major bottleneck for robot learning. High-fidelity interfaces often require costl
arXiv:2607.27212v1 Announce Type: cross Abstract: Children with Autism Spectrum Disorder in Arabic-speaking countries face compounded barriers to effective speech and language therapy: a shortage of q
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:2511.20722v2 Announce Type: replace Abstract: We introduce DinoLizer, a DINOv2-based localizer of manipulated areas in generative inpainting. The model is trained to focus on semantically altere
arXiv:2606.18997v2 Announce Type: replace Abstract: Uncovering the true informational architecture of real-world complex systems requires disentangling how their components uniquely store, redundantly
arXiv:2607.10099v2 Announce Type: replace Abstract: Gust disturbances, dynamic vertical inflow and ground effect are key adverse aerodynamic phenomena that induce variations in the forces acting on a
arXiv:2511.14117v2 Announce Type: replace Abstract: Supervised classifiers output a distribution over classes but are typically trained against a single label obtained by collapsing multiple annotator
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:2607.26773v1 Announce Type: new Abstract: Latent communication in large language model (LLM)-based multi-agent systems (MAS) transmits continuous internal representations instead of text, but gr
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:2607.28567v1 Announce Type: cross Abstract: Longitudinal causal studies often record histories as irregular functional fragments: laboratory values, physiologic signals, sensor streams, and imag
arXiv:2607.27558v1 Announce Type: new Abstract: Recovering Parametric CAD sequences from raster-format 2D Computer-Aided Design (CAD) drawings accumulated prior to digital transformation is important
arXiv:2607.27990v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) communicate through sparse binary spike events rather than dense activations, enabling energy-efficient inference on ne
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:2607.27614v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have led sign language translation (SLT), the task of converting sign-language videos into spoken-langua
arXiv:2607.27891v1 Announce Type: cross Abstract: Temporal graph learning is commonly organized around the evolution of node states or the encoding of interaction histories. We study an underexplored,
arXiv:2512.03661v2 Announce Type: replace Abstract: Activation steering has emerged as a powerful method for guiding the behavior of generative models towards desired outcomes such as toxicity mitigat
arXiv:2607.26201v1 Announce Type: cross Abstract: Security operations centers rely on anomaly detection systems to flag suspicious events. Feature-level explanations for anomaly detectors offer limite
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:2607.26588v1 Announce Type: new Abstract: The rapid development of large language models (LLMs) has renewed interest in agent-based modeling (ABM). However, current LLM-based ABM research faces
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
arXiv:2504.21174v2 Announce Type: replace Abstract: Deep learning drives a new wave in computing systems and triggers the automation of increasingly complex problems. In particular, Large Language Mod
arXiv:2607.28243v1 Announce Type: new Abstract: Egocentric video offers rich manipulation experience for embodied AI, yet collecting diverse egocentric data across scenes, objects, motions, and embodi
arXiv:2607.27755v1 Announce Type: new Abstract: We address the problem of recovering the full-body mesh from only the head pose. This task has become essential for various applications based on head-m
arXiv:2504.16616v4 Announce Type: replace Abstract: Event cameras, characterized by microsecond temporal resolution and very High Dynamic Range (HDR), emit high-speed event streams for perception task
arXiv:2607.28229v1 Announce Type: new Abstract: The web is increasingly accessed by AI agents rather than humans. Every agent needs knowledge, especially in the life-sciences, where agentic pipelines
arXiv:2511.19982v3 Announce Type: replace Abstract: Continuous emotional image content generation (C-EICG) is emerging rapidly due to its ability to produce images aligned with both user descriptions
arXiv:2607.27320v1 Announce Type: cross Abstract: Field-level inference of cosmological initial conditions from galaxy surveys requires a forward model that is simultaneously accurate in the non-linea
arXiv:2607.28020v1 Announce Type: new Abstract: Learned video compression relies on accurate temporal modeling to remove redundancy between adjacent frames. However, most existing codecs infer motion
arXiv:2607.28338v1 Announce Type: new Abstract: Clustered Federated Learning (CFL) addresses data heterogeneity in federated settings by grouping clients with similar data distributions to enable effe
arXiv:2607.27825v1 Announce Type: cross Abstract: Reconstructing dynamic surgical scenes is crucial for robot-assisted minimally invasive surgery; however, it continues to be difficult because of tiss
arXiv:2603.05950v2 Announce Type: replace Abstract: Visual token reduction is critical for accelerating Vision-Language Models (VLMs), since visual inputs are represented as token sequences that intro
arXiv:2607.28035v1 Announce Type: new Abstract: Irregular multivariate time series are widely encountered in applications such as healthcare monitoring, human activity recognition, and environmental s
arXiv:2507.18046v2 Announce Type: replace Abstract: Recent advances in AI-generated video have shown strong performance on text-to-video tasks, particularly for short clips depicting a single scene. H
arXiv:2512.15011v3 Announce Type: replace Abstract: Artificial intelligence (AI) increasingly generates the very content used to train future AI systems. This feedback loop can degrade model quality,
arXiv:2607.27723v1 Announce Type: cross Abstract: Engression (Shen and Meinshausen, 2024) learns a conditional distribution by fitting a generative model Y = f(X,arepsilon) under the energy score, a s
arXiv:2607.28582v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) is a promising approach to improve reasoning language models, but it remains brittle in practice: making it work reli
arXiv:2607.27655v1 Announce Type: new Abstract: Reported accuracy in electroencephalography (EEG) emotion recognition depends on the complete evaluation procedure, not only the classifier. We separate
arXiv:2607.26120v1 Announce Type: new Abstract: Large Language Models (LLMs)-powered multi-agent systems are increasingly deployed in mixed-motive environments, where agents operate under asymmetric i
arXiv:2607.27681v1 Announce Type: new Abstract: Transient-stability assessment determines whether a power system can recover after a disturbance and is therefore essential to preventing generator trip
Everyone’s going on about how smart Leopold Aschennbrenner is (or was). But 1. He obviously didn’t know anything at all about risk management. (Or arrogantly chose to disregard whatever he might have
arXiv:2607.26512v1 Announce Type: new Abstract: AI agents can draft claims faster than authors can check whether the cited or retrieved evidence supports them. We study evidence-ledger adjudication: a
arXiv:2607.27290v1 Announce Type: new Abstract: Modern telecommunication, cloud, and microservice systems emit correlated alarm cascades when components fail. Root cause analysis (RCA) aims to identif
arXiv:2607.27914v1 Announce Type: new Abstract: Multi-zone variable-air-volume control must balance thermal comfort, indoor air quality, and electricity use across several continuous actuators. Model
arXiv:2607.27522v1 Announce Type: new Abstract: As decision-making processes grow more complex, machine learning tools have become essential for tackling business and societal challenges. However, man
arXiv:2607.27280v1 Announce Type: cross Abstract: Robust Optimization Over Time (ROOT) is a recent branch of evolutionary dynamic optimization that seeks solutions capable of remaining effective acros
Here is my experience, which I would like to share with you and I also would like to hear your thoughts and valuable tips&tricks. Hardware: Mac Mini M4 (32GB Unified Memory) Model Server: Ollama Orche
arXiv:2607.28386v1 Announce Type: new Abstract: Image similarity underlies many computer vision applications, yet it is often unclear why two images receive a high or low similarity score. Existing ex
arXiv:2607.27372v1 Announce Type: cross Abstract: The deep learning revolution, kicked off by AlexNet, taught us that end-to-end training beats decomposing a problem into hand-designed stages. Generat
arXiv:2607.26367v1 Announce Type: new Abstract: An important skill in theoretical physics is to recognize when a new problem can be transformed into a known model. We study this skill as an AI-agent t
arXiv:2607.09306v3 Announce Type: replace Abstract: Behavioural auditing asks whether a language model behaves as it claims, but detection scores are reported without separating two targets: whether a
arXiv:2607.28596v1 Announce Type: new Abstract: In contact-rich manipulation, action multimodality and reactivity dominate different stages of a single episode. Before contact, multiple trajectories m
arXiv:2607.28129v1 Announce Type: new Abstract: Face-and-voice association learning is one of the most challenging tasks in deep learning. In this paper, we propose a simple but powerful cross-modal f