model releases

ConWriter: Transition-Constrained Stateful Long-Form Story Generation with Lightweight Neuro-Symbolic Consistency Control

arXiv:2608.05169v1 Announce Type: new Abstract: Long-form story generation requires models to preserve narrative consistency across extended contexts, yet existing prompting-based methods often accumu

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CREBench: Evaluating Large Language Models in Cryptographic Binary Reverse Engineering

DGX agent

arXiv:2604.03750v2 Announce Type: replace-cross Abstract: Reverse engineering (RE) is central to software security, particularly for cryptographic programs that handle sensitive data and are highly pr

model-releasesarxiv-cs-ai

7 Aug 2026

CRINN: Contrastive Reinforcement Learning for Approximate Nearest Neighbor Search

arXiv:2508.02091v4 Announce Type: replace-cross Abstract: Approximate nearest-neighbor search (ANNS) algorithms have become increasingly critical for recent AI applications, particularly in retrieval-

Cross-Architecture Steering Transfer in Language Models: A Systematic Empirical Study

arXiv:2608.05164v1 Announce Type: new Abstract: Independently trained large language models may develop shared internal representations of semantic concepts despite architectural differences -- but wh

D-CLOT: Double Closed Loop Optimal Transport for Unsupervised Action Segmentation

arXiv:2608.05877v1 Announce Type: cross Abstract: Optimal transport (OT) has emerged as an effective framework for unsupervised action segmentation. Yet, in existing OT-based methods, the latent actio

DASH: Decoupled Adaptive Surrogate - Acquisition Harness for Automated Bayesian Optimization

arXiv:2608.00641v2 Announce Type: replace Abstract: Bayesian optimization (BO) relies on a surrogate model and an acquisition function, yet the most suitable choices vary across tasks and optimization

DASH: Divergence-Adaptive Supervision Horizons for On-Policy Self-Distillation of Reasoning Models

arXiv:2608.06243v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) improves the reasoning capabilities of large language models using automatically verifiable outcom

Decoupling Perception from Description: Computation-Grounded Representation Alignment between Multivariate Time Series and Language

arXiv:2608.05238v1 Announce Type: new Abstract: Training multimodal models to align time series with language runs into a self-supervision trap. The usual recipe asks an LLM to read a series and write

Deep Generalised Mixed Models: a Novel Neural Network Structure for Analysing Hierarchical Data

arXiv:2608.05930v1 Announce Type: cross Abstract: The experience sampling method (ESM) is a longitudinal research design where participants report their thoughts, emotional states and behaviours multi

DeepSeek-V4-Flash-0731 is now fully rolled out as the new default for deepseek-v4-flash on Ollama's cloud. This model combines speed, effici…

DeepSeek-V4-Flash-0731 is now fully rolled out as the new default for deepseek-v4-flash on Ollama's cloud. This model combines speed, efficiency, and frontier-level performance. Fast: 120+ output tps

model-releasesollama--x

Domain-Grounded Candidate Selection for Agentic Image Editing: A Shadow Removal Case

arXiv:2608.06075v1 Announce Type: cross Abstract: Commercial vision-language models are reshaping computer vision, with visual priors broad enough to rival task-specific systems. This raises a natural

DREAM: LLM-based Dynamic Role-playing via Event-Aware Memory Graph

arXiv:2608.05170v1 Announce Type: cross Abstract: Role-playing agents (RPAs) have emerged as a key application of large language models, enabling immersive and high-fidelity character simulation. Accu

Dual-space posterior sampling for Bayesian inference in constrained inverse problems

arXiv:2603.00393v2 Announce Type: replace-cross Abstract: Inverse problems constrained by partial differential equations are often ill-conditioned due to noisy, incomplete data or inherent non-uniquen

Dynamic Graph Prompting via Topology-Routed Mixed-Curvature Experts

arXiv:2608.06031v1 Announce Type: new Abstract: Dynamic graph prompting freezes a pre-trained temporal backbone and adapts it to label-scarce downstream tasks using lightweight prompts. However, exist

DynaPix: Can Vision-Language Models Identify the Exact Future?

arXiv:2608.05505v1 Announce Type: new Abstract: Acting in a physical scene requires knowing its real later state, not a plausible one. Current evaluations often accept words or a realistic-looking ima

ECHO: A Locally-Deployable Agentic Health Assistant with Temporal Memory, Safety Guardrails, and Speech Assessment

arXiv:2608.06110v1 Announce Type: new Abstract: This paper presents ECHO (Enhanced Care & Health Observer), a locally-deployable conversational health assistant for long-term chronic care management.

Echo Dot 2 can run 28M LLM at decent speed

Code and instructions available here: https://github.com/albertoZurini/echo-dot-2-playground Hello there! After a few days of experimenting I was able to get a completely local voice pipeline running

EcoAgent-Bench: Evaluating Economic Decision-Making in Budget-Constrained LLM Agents

arXiv:2608.05519v1 Announce Type: new Abstract: Agent benchmarks usually measure task completion and treat resource use as an auxiliary statistic. In deployment, however, the choice among a local look

Effective pruning of task-trained recurrent neural networks using noisy fluctuations and connection rescaling

arXiv:2608.05464v1 Announce Type: cross Abstract: The pruning of network connections is key to brain function but, despite its importance, there exist few biologically-plausible pruning rules with dem

Energy-Guided Flow Matching

arXiv:2608.05811v1 Announce Type: new Abstract: Pixel-space generative models bypass lossy latent compression, yet necessitate joint learning of global structure and fine-grained details in a high-dim

Enhancing Anomaly Resilience in Research Networks: A Large-Scale Forecasting Benchmark for Dynamic Security Baselining

arXiv:2608.05605v1 Announce Type: cross Abstract: Research and Education Networks (RENs) serve as critical infrastructure for scientific discovery, yet they face a unique security paradox: their norma

Enhancing Social Intelligence in LLMs with Hierarchical Reasoning and Utterance-Level Goal Rewarding

arXiv:2608.05832v1 Announce Type: new Abstract: Large language models (LLMs) excel in structured tasks but struggle with dynamic social interactions, where success requires long-term goal coordination

EpiBench: Can LLMs Understand Epitopes for Antibody Drug Discovery?

arXiv:2608.06022v1 Announce Type: new Abstract: Epitopes determine where antibodies bind antigens and shape downstream therapeutic properties such as functional blockade and escape resistance, making

Equation-Free Period-Aware Forecast-Error Contraction for Estimating Negative Largest Lyapunov Exponents from Short Trajectory Ensembles

arXiv:2608.05522v1 Announce Type: cross Abstract: Estimating positive largest Lyapunov exponents from data is comparatively natural because neighboring trajectories separate, whereas stable dynamics r

EschaLabs/Qwen3.6-35B-A3B-Escha-W2 · Hugging Face

Hey peeps. I know you're tired of low quants giving hard to believe numbers. I'm quite skeptical too and from what I tried I'm often left with the impression that the claims fall short. So this model

Evaluating and Improving Pedagogical Fit in LLM-Based AI Tutors with the Pedagogical Suitability Index

arXiv:2608.05411v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as AI tutors, but a correct answer is not always a pedagogically appropriate one. In classroom learni

Evaluating Investment Logic in Large Language Models: A Real-World Benchmark Towards Personalzied Financial Agents

arXiv:2608.06108v1 Announce Type: new Abstract: Investment competence is inherently personalized: the same market evidence can justify different actions for investors with different goals, horizons, p

Everyone should pay attention to the training timelines in this video. OpenAI shares they started training a new internal model May 7. That …

model-releasesallie-k--miller--x

Everyone should pay attention to the training timelines in this video. OpenAI shares they started training a new internal model May 7. That is more than two months before they released GPT-5.6 publicl

Evidence Lock Before Commitment: A Frozen Interface Degrades LLM-as-Judge Evaluation

arXiv:2608.05353v1 Announce Type: new Abstract: LLM judges are often asked to extract criteria and evidence before choosing between candidate answers. This workflow assumes that the intermediate recor

Evidential Rule Learning for Interpretable Classification with Abstention

arXiv:2608.05859v1 Announce Type: cross Abstract: Interpretable classification often requires more than accurate predictions for real-life deployment: models should be transparent about the evidence b

EvReflection: Event-Driven Micro-Dynamics for Reflection Removal

arXiv:2608.06184v1 Announce Type: new Abstract: Despite remarkable progress in reflection removal, current methods primarily exploit static image priors from a single frame and still suffer from sever

FinEvo-Bench: A Longitudinal Benchmark for Self-Evolving Agents in Professional Financial Workflows

arXiv:2608.06144v1 Announce Type: new Abstract: Most agent benchmarks evaluate tasks independently and cannot measure whether experience from one task helps with later tasks. Existing self-evolution b

FormBharo: Designing and Evaluating a Voice Agent for Conversational Form Filling in Rural India

arXiv:2608.06027v1 Announce Type: cross Abstract: In India, almost every social benefit starts with a form, yet the people who need these benefits most are often unable to read or write. Reaching them

From Sports to Safety: Benchmarking Proactive Risk Inference in MLLMs

arXiv:2608.05560v1 Announce Type: cross Abstract: Timely anticipation of physical hazards is essential for real-world safety, yet existing MLLM evaluations focus on harmful content or general risks, l

GAUGE: A Measurement-Grounded Benchmark for Physical Fidelity in Simulation Engines and Video World Models

arXiv:2608.05948v1 Announce Type: new Abstract: Physics engines facilitate large-scale training and evaluation for embodied intelligence, while generative video world models are emerging as implicit s

Gemma 4 QAT could be improved further by Google aligning the QAT model to modern q4_k instead of q4_0

Hello, For the past few days I have been benchmarking Gemma 4 26b QAT UD Q4_K_XL extensively versus Bartowski's Q4_K_L. While QAT is certainly very effective and reducing memory consumption versus the

good grok

model-releasesyohei-nakajima--x

good grok Best match for this hierarchical hands-free setup: - Runtime: ActiveGraph (event-sourced log as source of truth) or LangGraph for supervisor/manager graphs - Roles as skills: Claude Agent SD

Got job as Director of AI and Systems development self-taught

Hey everyone, I just wanted to share my journey here for some motivation. Three years ago, I saw the sudden spike in AI and realized it was the future of tech. My goal at the time was to be an indie g

GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning

arXiv:2604.02721v3 Announce Type: replace Abstract: Competitive programming remains one of the last few human strongholds in coding against AI. The best AI system to date still underperforms the best

Grok Build V1.0 is now released. Try it out! http://X.ai/build

model-releaseselon-musk--x

Grok Build V1.0 is now released. Try it out! http://X.ai/build 🚨 NEW GROK BUILD UPDATE 🚨 Grok Build v1.0.0 is now live. SpaceXAI is pushing new Grok Build updates almost daily. Updates: UI & navigatio

GROM: Gradient-Free Rapid One-Shot Machine Unlearning

arXiv:2608.05783v1 Announce Type: cross Abstract: Machine unlearning has become a critical capability for safely removing specific, sensitive knowledge from large language models (LLMs). Current state

Grounded Well-Condition Anomaly Detection on the Volve Field: Constructed Labels, a Baseline, and a Dual-Head Model

arXiv:2608.05685v1 Announce Type: new Abstract: Most public benchmarks for machine-condition monitoring come from test rigs, where faults are induced on purpose and every event is known. Real producti

GST-Bench: Can VLMs Develop Global Spatial Awareness from Video?

arXiv:2608.05747v1 Announce Type: new Abstract: Spatial intelligence is fundamental to embodied agents, yet existing benchmarks focus on local spatial perception from single or few viewpoints, overloo

Hardware Keystores for AI Agent Signing Workflows: A Zero-Trust MCP Enforcement Architecture

arXiv:2608.06130v1 Announce Type: cross Abstract: AI agents performing cryptographic operations (signing Git commits, authenticating API calls, issuing certificates) currently store private keys in so

HarnessOpt-Bench: Evaluating LLMs at Harness Optimization

arXiv:2608.06301v1 Announce Type: new Abstract: As LLMs are increasingly deployed within agentic systems, their capabilities depend not only on the model weights but also on the harness: the prompts,

HERALD: Counterfactual Audits and Minimal Repairs for Proof-of-Retrieval Rewards

arXiv:2608.06012v1 Announce Type: new Abstract: Search-agent rewards mix answer quality, citation grounding, tool cost, and anti-hacking terms; a high score therefore need not imply that cited evidenc

Hijacking Robots with a Piece of Paper: A Systematic Study of Physical Prompt Injection in VLM-Controlled Robots

arXiv:2608.05715v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as planners in robotic systems, where they translate natural-language commands into executable

How Google Cloud detects, contains, and protects against emerging threats

model-releasesgoogle-cloud-ai

At Google Cloud, securing your data and business systems is our foundational commitment. We empower our customers with the tools, governance, and infrastructure needed to securely deploy workloads and