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What We Know about Responsible AI Practices in Industry: A Half Decade of Empirical Research

arXiv:2608.10431v1 Announce Type: cross Abstract: Responsible AI (RAI) has become a central concern for technology companies, regulators, and the public. How industry practitioners interpret, implemen

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Applications

When Repository Labels Are Not Image-Level Truth: A Supervision Auditing Framework for Chest Radiograph AI

DGX agent

arXiv:2608.10084v1 Announce Type: cross Abstract: Public chest X-ray repositories are widely used to train medical AI systems, yet their labels are typically extracted from radiology reports rather th

applicationsarxiv-cs-cv

12 Aug 2026

Why Does CLAUDE.md Keep Growing? Catastrophic Remembering in Agentic Coding

arXiv:2608.11095v1 Announce Type: new Abstract: Agentic coding READMEs like CLAUDE.md grow without bound in real repositories, stopping only when the repository retires or someone rewrites the file wh

With the smartest person I know, @HarshSensei, we're building evsys-sdk for the community, this open-source repository allows anyone to buil…

model-releasesfireworks-ai--x

With the smartest person I know, @HarshSensei, we're building evsys-sdk for the community, this open-source repository allows anyone to build their own continual learning system with first-class suppo

XCoT-VLA: Executable Chain-of-Thought for Vision-Language-Action Driving

arXiv:2608.10976v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models can connect scene understanding, semantic reasoning, and trajectory generation for autonomous driving. However, verb

Beyond Pixels: Exploring DOM Downsampling for LLM-Based Web Agents

arXiv:2508.04412v3 Announce Type: replace Abstract: The advent of large language models (LLMs) has sparked an evolution of autonomous web browsing agents: given a web browsing task and serialised user

Distill Skills into Weights, Not Prompts: Abstract Skills as Privileged Signals for On-Policy Self-Distillation

arXiv:2608.09826v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards yields no group-relative signal when rollout groups are uniformly correct or uniformly wrong, which acc

EvoTrustRAG: Evolution-Aware Conflict Attribution and Evidence Handling for Reliable Retrieval-Augmented Generation

arXiv:2608.07933v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves the factuality of large language models with external knowledge, yet conflicting evidence remains a fund

Expert-Guided Multimodal Fusion for Unified Emotion and Sentiment Analysis

arXiv:2601.07565v2 Announce Type: replace-cross Abstract: Multimodal emotion understanding requires the integration of heterogeneous data sources, including text, audio, and visual modalities, while s

flowengineR: A Modular and Extensible Framework for Fair and Reproducible Workflow Design in R

arXiv:2511.00079v2 Announce Type: replace Abstract: flowengineR is an R package designed to provide a modular and extensible framework for building reproducible algorithmic workflows for general-purpo

safetyarxiv-cs-lg

Goose: Anisotropic Speculation Trees for Training-Free Speculative Decoding

arXiv:2604.02047v2 Announce Type: replace-cross Abstract: Speculative decoding accelerates large language model inference by drafting multiple candidate tokens and verifying them in a single forward p

HSMLA: Hierarchical Softmax Multi-scale Linear Attention for Efficient Vision Transformers

arXiv:2608.07616v1 Announce Type: new Abstract: Vision transformers face significant computational overheads in high-resolution dense prediction due to the quadratic complexity of self-attention. Line

local-aiarxiv-cs-cv

I put Gemma 4 E4B and E2B into an e-reader so I can ask my weird questions and share my thoughts in private directly in app.

model-releasesr-localllama

Here's how it works in the app: Framework: Runs on LiteRT-LM (like Google's AI Edge). Models: Downloads either the E2B (~2.5 GB) or E4B (~3.6 GB) INT4 quantized models directly from ungated litert-com

In-Loop Model Adaptation with Coupled Latent-Noise Guidance for High-Fidelity Subject-Driven Text-to-Image Generation

arXiv:2608.09244v1 Announce Type: new Abstract: Text-to-image diffusion models have achieved remarkable success in generating high-quality images from a given text prompt. Subject-driven generation ai

safetyarxiv-cs-cv

InstructionCrafter: Generating Consistent and High-Fidelity Visual Instructions

model-releasesarxiv-cs-cv

arXiv:2608.08460v1 Announce Type: new Abstract: Given textual task instructions, generating step-by-step visual instructions as an image sequence requires the simultaneous satisfaction of multiple pro

Intent Speaks Louder: Controllable User Simulation Beyond Response Imitation

arXiv:2608.09420v1 Announce Type: new Abstract: User simulators are widely used as scalable environments for training and evaluating interactive assistants. Generating the next user turn is inherently

safetyarxiv-cs-cl

Jako Tako or Fluent? Presenting PoVisLE: A Polish Vision-Language Evaluation

arXiv:2608.07763v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance on tasks such as image captioning, visual question answering, and image-to-text generatio

Learning Preference Adaptation for Large Language Model Personalization via Verbal Reinforcement Learning

arXiv:2608.09507v1 Announce Type: cross Abstract: Natural language user preferences provide an interpretable interface for LLM personalization. However, universal preference summaries often contain in

LogiShot: Logically Coherent Cross-Shot Video Generation

model-releasesarxiv-cs-cv

arXiv:2608.08820v1 Announce Type: new Abstract: Generating cross-shot videos that are logically connected is essential for content creation. Currently, most cross-shot video-generation workflows, such

MateInfoUB: A Real-World Benchmark for Testing LLMs in Competitive, Multilingual, and Multimodal Educational Tasks

arXiv:2507.03162v2 Announce Type: replace-cross Abstract: The rapid advancement of Large Language Models (LLMs) has transformed various domains, particularly computer science (CS) education. These mod

Measuring the Tokenization Premium: A Cost Audit for Underserved Language Communities

arXiv:2608.09046v1 Announce Type: new Abstract: Large language models are increasingly deployed as general-purpose educational and technical assistance systems, but their underlying infrastructure doe

Mitigating Over-Personalization in LLMs via Structured Memory

arXiv:2608.08300v1 Announce Type: new Abstract: Conversational assistants increasingly rely on persistent long-term memory to personalize responses across sessions. However, when stored user informati

Muse-Glimmer 30B Hits ~280 t/s in Real Production Coding

model-releasesr-localllama

These numbers were captured during a real feature implementation task in Next.js and Nest.js (adding a theme switching system across components). The structural predictability of UI/state refactoring

North Africa's Missing Framework: NLP-Driven Mental Healthcare in Algeria and Implications for Low-resource Settings

arXiv:2608.08607v1 Announce Type: new Abstract: Mental health disorders are a leading cause of disability worldwide, yet Natural Language Processing (NLP) research for mental healthcare has remained c

safetyarxiv-cs-cl

PRISM-Delta: Differential Subspace Steering for Prompt Highlighting in Large Language Models

arXiv:2603.10705v2 Announce Type: replace Abstract: Prompt highlighting steers a large language model to prioritize user-specified text spans during generation. A key challenge of existing Key-editing

researcharxiv-cs-cl

PROSLEX: A Novel Dataset for Expert-Annotated Legal Statute Prediction for Indian Judiciary

arXiv:2608.08830v1 Announce Type: new Abstract: Legal Statute Prediction (LSP) involves automatically identifying relevant legal statutes given factual descriptions in legal documents, typically frame

RayLift: Lifting Complementary Ray-Wise Evidence with 3D Geometry Priors for Semantic Scene Completion

arXiv:2608.08476v1 Announce Type: new Abstract: Camera-based 3D semantic scene completion (SSC) provides comprehensive scene understanding for autonomous driving and robotics. However, existing method

local-aiarxiv-cs-cv

Reducing Pretraining-Generation Mismatch in Diffusion Language Models

arXiv:2608.09424v1 Announce Type: new Abstract: Autoregressive language models align training and use: generation conditions on a clean prompt, and training predicts future tokens from clean left cont

RotaryQuant: Fitting 120B MoE Models on Consumer Hardware via Fused Compressed-Space Attention

model-releasesarxiv-cs-lg

arXiv:2608.08081v1 Announce Type: cross Abstract: Large mixture-of-experts (MoE) language models with 26--120 billion parameters exceed the memory capacity of consumer devices through three simultaneo

Applications

Search over the Visual World: Persistent Visual Memory, Layered Indexes, and Source-Grounded Evidence

arXiv:2608.08075v1 Announce Type: cross Abstract: Most video-retrieval systems assume a bounded corpus and return ranked files or timestamps. Agents operating over cameras, screens, streams, and archi

applicationsarxiv-cs-cv

SkillSmith: Enhancing Locally Deployed Agents via Automatic Skill Construction and Evolution

arXiv:2608.08037v1 Announce Type: new Abstract: LLM-based agent frameworks now act as personal assistants for multi-step tasks. Existing agent frameworks such as OpenClaw commonly follow the Cloud Age

local-aiarxiv-cs-ai

SPRInG: Continual LLM Personalization via Selective Parametric Adaptation and Retrieval-Interpolated Generation

arXiv:2601.09974v2 Announce Type: replace Abstract: Personalizing Large Language Models typically relies on static retrieval or one-time adaptation, assuming user preferences remain invariant over tim

VeinCast: Physics-Guided Dynamic Field Graphs with Graph-Conditioned Fusion for Global Medium-Range Weather Forecasting

arXiv:2608.09286v1 Announce Type: cross Abstract: Global medium-range weather forecasting requires modeling structured yet state-dependent interactions among heterogeneous atmospheric fields. Existing

AfriNLLB: Efficient Translation Models for African Languages

arXiv:2602.09373v2 Announce Type: replace Abstract: In this work, we present AfriNLLB, a series of lightweight models for efficient translation from and into African languages. AfriNLLB supports 15 la

researcharxiv-cs-cl

AnyTrack: Unifying Visual Object Tracking with Any Modalities

arXiv:2608.06773v1 Announce Type: new Abstract: Visual object tracking aims to continuously locate specific targets within sequential frames, evolving from single-modal methods to multi-modal ones. Ho

researcharxiv-cs-cv

Bootstrap-Conditioned Action Selection with Tabular Foundation Models

arXiv:2608.06559v1 Announce Type: new Abstract: Contextual bandits offer a natural framework for sample-efficient personalization, but practical deployment remains difficult under sparse, biased inter

safetyarxiv-cs-lg

Bridging the Gap Between Hyperdimensional Computing and Kernel Methods via the Nystrom Method

arXiv:2608.06860v1 Announce Type: cross Abstract: Hyperdimensional computing (HDC) is an approach from the cognitive science literature for solving information processing tasks using data represented

Applications

Can MLLMs Decode the Creative Leap? Introducing C4 for Cross-Concept Understanding

arXiv:2608.06501v1 Announce Type: new Abstract: Creative capabilities of MLLMs matter in design, communication, education, and human--AI collaboration, yet remain difficult to evaluate because explici

applicationsarxiv-cs-ai

DAEP: Difficulty-Aware Evidence Planning for Medical Video Corpus Temporal Answer Grounding

arXiv:2608.06869v1 Announce Type: cross Abstract: We describe DAEP, team BIGC's submission to NLPCC 2026 Shared Task 1 Track 3: Difficulty-Aware Temporal Answer Grounding in Video Corpus (DA-TAGVC). T

local-aiarxiv-cs-cl

Agents

Explicit, Not Longer: What Makes Epistemic Stance Survive Memory Compression

arXiv:2608.06953v1 Announce Type: cross Abstract: Agent memory systems compress what they store, and compression is built to drop qualifiers, so a claim's epistemic standing tends not to survive being

agentsarxiv-cs-ai

Foundation Models Adaptation for Multi-View Multi-modal Cardiac MRI Segmentation and Direct Ejection Fraction Estimation

arXiv:2608.07291v1 Announce Type: new Abstract: Foundation models have shown strong transferability in cardiac MRI (CMR), but their effectiveness for heterogeneous multi-view and multi-sequence CMR an

researcharxiv-cs-cv

From Test-Time Scaling to Reusable Memory: Measuring Crystallization in Text-to-SQL

arXiv:2608.07213v1 Announce Type: new Abstract: Test-time scaling can correct difficult text-to-SQL queries, but the extra computation is normally discarded after each answer. Systems increasingly ret

researcharxiv-cs-cl

Google named a Leader in The Forrester Wave™: AI Platforms, Q3 2026

model-releasesgoogle-cloud-ai

At Google Cloud, we help organizations of all sizes build and operationalize complex agentic workflows with total confidence. By combining world-class AI research with an open, fully integrated AI pla

How Malachyte solves retail’s cold-start problem with managed real-time AI

What’s the best way to recommend products to little-known users? We’ve spent our careers trying to solve this problem for major companies like Spotify and Priceline, and it’s why Sidd founded Malachyt

local-aigoogle-cloud-ai

INTRYGUE: Induction-Aware Entropy Gating for Reliable RAG Uncertainty Estimation

arXiv:2603.21607v2 Announce Type: replace Abstract: While retrieval-augmented generation (RAG) significantly improves the factual reliability of LLMs, it does not eliminate hallucinations, so robust u

Modular TTT: Rethinking Test-Time Training as Composable Modules

arXiv:2608.07110v1 Announce Type: cross Abstract: Test-time training (TTT) views sequence modeling as an online learning problem in which fast weights are updated by an internal learning rule. Despite

Multimodal Drivers' Emotion Recognition and Safety-Oriented Intervention for Intelligent Transportation Systems

arXiv:2608.06378v1 Announce Type: cross Abstract: Driver emotions can affect risk perception, decision-making, and vehicle control under complex road conditions. Existing studies mainly focus on drive

Needle 2: 14MB agentic LLM for phones, wearables, smart home and robots.

model-releasesr-localllama

Hey LocalLlaMa, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots a