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Harmful Content Is Not Enough: Continuation Framing Moderates In-Context Emergent Misalignment

arXiv:2608.08212v1 Announce Type: new Abstract: In-context learning (ICL) can induce emergent misalignment (EM), where narrow misaligned examples alter answers to unrelated questions. Existing prompts

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Research

Harnessing Abundance: A Generativity Perspective on Human-GenAI Collaboration

DGX agent

arXiv:2608.07500v1 Announce Type: cross Abstract: Research on human-GenAI collaboration yields conflicting findings: GenAI can enhance creativity yet reduce collective diversity, with uneven benefits

researcharxiv-cs-ai

11 Aug 2026

Local Ai

HarnessWAM: Bridging Prediction and Deliberation in World Action Models

arXiv:2608.09516v1 Announce Type: new Abstract: World Action Models (WAMs) jointly learn environmental dynamics and robot actions, introducing priors over physical evolution into embodied control. How

local-aiarxiv-cs-ro

HeatCast: A Benchmark for Neighborhood-Scale LST Forecasting across 124 U.S. Cities

model-releasesarxiv-cs-cv

arXiv:2608.07640v1 Announce Type: new Abstract: Land Surface Temperature (LST) is a widely used satellite-derived measure of urban surface heat, but there is no shared benchmark for forecasting it at

Hidden Language Consistency Phenomena in Reasoning LLMs

arXiv:2608.08447v1 Announce Type: cross Abstract: Multilingual reasoning models are commonly evaluated by whether they arrive at the correct answer, but not by whether they preserve the intended langu

Agents

Hierarchical Fast--Slow ReAct Agent for Zero-Shot Object-Goal Navigation

arXiv:2608.09816v1 Announce Type: new Abstract: Zero-shot object-goal navigation (ZSON) requires a robot to find a named object category in a building it has never entered. The prevailing approach sco

agentsarxiv-cs-ro

Hierarchical Multi-Task Federated Learning in VANETs

arXiv:2608.08111v1 Announce Type: cross Abstract: Vehicular Ad hoc Networks (VANETs) increasingly rely on federated learning (FL) to enable collaborative intelligence without sharing raw sensory data.

Hierarchical rank-evolving representation for physics-informed neural networks

arXiv:2608.09483v1 Announce Type: new Abstract: Recently, tensor-based physics-informed neural networks (T-PINNs) have received increasing attention. However, existing T-PINNs still face a fundamental

applicationsarxiv-cs-lg

Hierarchical Self-Improvement: A Framework for Task-Specific Evolvable Agent Harnesses

arXiv:2608.08466v1 Announce Type: new Abstract: Modern LLM agents are often improved by modifying prompts, tools, or workflows manually, while the executable scaffold surrounding the model---the harne

Hierarchical Topology-Aware Planning and Control of Underwater Vehicle-Manipulator Systems in Confined Environments

arXiv:2608.08871v1 Announce Type: new Abstract: This paper addresses autonomous intervention with an underwater vehicle--manipulator system (UVMS) in confined, cluttered, and partially known environme

safetyarxiv-cs-ro

High-Capacity Generalized Hopfield Networks

arXiv:2608.08226v1 Announce Type: cross Abstract: Generalized Hopfield networks are introduced where memories and neurons are continuous variables that lie on a Riemannian manifold. We explicitly focu

safetyarxiv-cs-cv

High Fidelity Capture, Reconstruction, and Transfer of Human Demonstrations for Robot-Assisted Bathing

model-releasesarxiv-cs-ro

arXiv:2608.09127v1 Announce Type: new Abstract: Despite the demand for robots in high-value clinical tasks like bathing, contemporary systems still lack the safety and reliability required for complex

High-Layer Attention Pruning with Rescaling

model-releasesarxiv-cs-cl

arXiv:2507.01900v3 Announce Type: replace Abstract: Pruning is a highly effective approach for compressing large language models (LLMs), significantly reducing inference latency. However, conventional

High-Quality Exposure Correction with Diffusion-Based Image Generation Priors

arXiv:2608.08720v1 Announce Type: new Abstract: Although most existing exposure correction methods achieve high fidelity, they often place excessive focus on overall pixel-wise accuracy, making it cha

researcharxiv-cs-cv

HindsightBench: A Black-Box Behavioral Audit Protocol for Parametric Hindsight in Time-Indexed LLM Decision Tasks

arXiv:2607.18867v2 Announce Type: replace-cross Abstract: Large language models leak parametric knowledge of what followed a historical date into decision tasks indexed by that date -- not necessarily

researcharxiv-cs-cl

Hit Selection Using SSMD-Based Machine Learning Performance Metrics in High-Throughput Screening Assays

arXiv:2608.07609v1 Announce Type: cross Abstract: High-throughput screening (HTS) assays are central to early-stage drug discovery but are often limited by extreme data sparsity, as primary screens ty

Hardware

Holder Signed Distance: A Differentiable, Signed, Parallelizable Metric for Robotics

arXiv:2608.07707v1 Announce Type: new Abstract: Computing distances between sets is essential in robotic motion planning and control, where differentiable gradients enable real-time optimization. The

hardwarearxiv-cs-ro

HoloAegis: Frozen Representation, Topological Inference: Minimally Parametric Safety Manifolds for Zero-Shot LLM Guardrails

arXiv:2608.08485v1 Announce Type: new Abstract: Current LLM safety guardrails face a fundamental tension: fine-tuning distorts pre-trained representations while generative judges incur prohibitive inf

safetyarxiv-cs-ai

HonestFace: Towards Honest Face Restoration with One-Step Diffusion Model

arXiv:2505.18469v2 Announce Type: replace Abstract: Face restoration has achieved significant advancements through the years of development. However, maintaining high fidelity and authenticity while a

safetyarxiv-cs-cv

HOPPER: Learnable Hop Extraction for Linearized Graph Sequence Models

model-releasesarxiv-cs-lg

arXiv:2608.09031v1 Announce Type: new Abstract: Graph neural networks typically propagate information through repeated message-passing layers, coupling the distance over which information travels with

How Can Rhetoric Reward-Hack AI Reviewers? Dissecting Rhetorical Sensitivity in AI-Based Peer Review

arXiv:2608.08975v1 Announce Type: cross Abstract: As large language models increasingly participate in scientific evaluation, we investigate a potential form of reward hacking: how rhetorical choices

How Do Large Language Models Judge Social Attraction? Evidence from Theory-Grounded Persona Ratings Across Multiple LLMs and Humans

arXiv:2608.09717v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to perform subjective evaluations traditionally made by humans, yet their validity as social judges

How Far Do Foundation Models Transfer to Infant Signals? A Cross-Dataset Transfer Audit with a Unified Need Ontology

arXiv:2608.08989v1 Announce Type: cross Abstract: Public infant cry corpora are small, label-incompatible, and almost always evaluated one corpus at a time. We ask what this practice hides and what fi

How Much Backtracking is Enough? Exploring the Interplay of SFT and RL in Enhancing LLM Reasoning

arXiv:2505.24273v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) suggest that reinforcement learning (RL) effectively internalizes search strategies, yielding si

How Much Does It Cost to Answer My Question? Benchmarking Cloud VLM-based VQA Systems

model-releasesarxiv-cs-cv

arXiv:2608.07861v1 Announce Type: new Abstract: Vision-language models (VLMs) are becoming a practical backend for mobile visual question answering (VQA) systems, enabling smartphones and smart glasse

How ONESTRUCTION built the Ishigaki-IDS foundation model with AWS GenAIIC

ONESTRUCTION, with technical advisory from the AWS Generative AI Innovation Center, built Ishigaki-IDS, a foundation model specialized for construction and BIM workflows. This architectural case study

applicationsaws-ml-blog

How People Evaluate AI-, Expert-, and Peer-Style Financial Advice

arXiv:2608.09019v1 Announce Type: cross Abstract: As generative AI increasingly becomes a common source of daily decision-making, including financial choices, it is critical to understand how people e

Tutorials

How Pixieset achieved 35% AI feature adoption by solving the right problem with Amazon Bedrock

Photographers are among the most skeptical audiences for generative AI. Learn how Pixieset used Amazon Bedrock to launch an AI-generated alt text feature to millions of users in four months, reaching

tutorialsaws-ml-blog

How sensitive do we want AI to be? Socio-communicative competencies of large language models in healthcare

arXiv:2608.07511v1 Announce Type: cross Abstract: Background. Effective clinical practice relies heavily on the socio-communicative skills of medical professionals. Large language models (LLMs) have b

How Simple Can It Get? From Interpretable Equations to Readable Rules for Financial Decision Making

arXiv:2608.09433v1 Announce Type: cross Abstract: In regulated domains such as finance, a model that cannot be explained cannot be deployed, yet many interpretable classifiers defeat their own purpose

applicationsarxiv-cs-ai

How to Ask the AI: A User Perspective Survey for Large Language Model Prompting

arXiv:2608.07494v1 Announce Type: cross Abstract: AI tools like ChatGPT and DeepSeek, powered by Large Language Models (LLMs), allow users to obtain instant and effective content responses simply by t

Local Ai

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

HugSelect: An Explainable Multi-Criteria Decision-Support Framework for foundation-model selection

arXiv:2608.08069v1 Announce Type: cross Abstract: Foundation models are increasingly reused as software components, making model selection a critical software-engineering decision. Current model hubs

Human-Guided Causal Knowledge Injection for Virtual Cells

arXiv:2608.08430v1 Announce Type: cross Abstract: Virtual cells employ machine learning models to simulate and predict cellular behaviors, serving as a critical computational framework for investigati

applicationsarxiv-cs-ai

Agents

HUMAN HARNESS! @mcuban casually made up the term when talking abt how we differentiate when everyone can create same thing/agent. Empathy, P…

HUMAN HARNESS! @mcuban casually made up the term when talking abt how we differentiate when everyone can create same thing/agent. Empathy, Personal Brand, using time agents save you to offer unique hu

agentsallie-k--miller--x

Human-Level Text-to-SQL via Reinforcement Learning on Verified Data, Without Pipeline Engineering

arXiv:2603.20004v3 Announce Type: replace-cross Abstract: Translating natural language questions to SQL queries (Text-to-SQL) is a long-standing problem in database research. Recent efforts have focus

researcharxiv-cs-cl

Hybrid Mamba-Attention Neural Architecture for Channel Estimation

arXiv:2601.17108v3 Announce Type: replace-cross Abstract: This paper proposes a hybrid Mamba-attention neural architecture to achieve improved channel estimation for orthogonal frequency-division mult

Hybrid Neural-Classical Correction for Frozen Time Series Foundation Models: A Comprehensive Ablation Study on High-Frequency Stock Prediction

arXiv:2608.08825v1 Announce Type: cross Abstract: Foundation models for time series forecasting demonstrate impressive zero-shot generalization but often underperform on specialized domains such as hi

applicationsarxiv-cs-ai

Hyperbolic Multimodal Continual Learning

arXiv:2608.09572v1 Announce Type: new Abstract: Hyperbolic geometry has recently emerged as a powerful representation space for multimodal learning, as it naturally captures hierarchical semantic stru

researcharxiv-cs-lg

HyperFake: Hyperspectral Reconstruction and Attention-Guided Analysis for Advanced Deepfake Detection

arXiv:2505.18587v2 Announce Type: replace-cross Abstract: Deepfakes pose a significant threat to digital media security, with current detection methods struggling to generalize across different manipu

I built a weird, low-power llama.cpp server using an Intel N100 + RTX 5060Ti

Everything started with the sudden death of my old ASRock J1900. While looking for the perfect ITX replacement, I stumbled upon the Chinese CW-NAS-ADLN-K motherboard, which looked perfect on paper: In

I gave DeepSeek V4 Flash basic vision by training a 40M connector on 100K examples

I wanted to find out whether a huge text-only MoE could be given basic vision without retraining the language model itself. The short answer is yes. I froze DeepSeek V4 Flash and a 417M-parameter Moon

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.

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

I ran Muse Glimmer @ 1M context - All tests passed.

Heeeey all! I just completed some fun tests with Muse Glimmer, I thought I'd let you know. In fact, the summary below was written by Muse itself! I ran a 2× DGX Spark cluster and got Meta's day-old Mu

I tested the CMP170HX

Lots of rumor and misinfo bouncing around, so I put some of these old mining cards to the test. I used 4 of the 8GB cards, set to 64GB each. Lots of models fit entirely on a single card, and you can a

Local Ai

I will be parting with my 4x Spark Cluster.

Laid off then my partner of 10 years said he's leaving, have to move, etc... I will post the r/hardwareswap link when I make it. I'm willing to add some incentive for r/LocalLLaMA folks. I will also a

local-air-localllama

Industry

I will pay 1 million for a developer to build this

I WILL PAY 1 MILLION FOR THIS 😭 I will literally pay 1,000,000 to the developer who fixes this. ChatGPT macOS: ⌘C text → ⌘Tab back to ChatGPT → ⌘V …and the search box ISN’T FOCUSED. 🤦‍♂️ Why do I have

industryr-chatgpt

Hardware

IBM and Together AI sign a $240M, multi-year deal to build an AI inference cluster on IBM Cloud, using Nvidia's HGX B300 systems, to support open-source models (Anhata Rooprai/Reuters)

Anhata Rooprai / Reuters: IBM and Together AI sign a 240M, multi-year deal to build an AI inference cluster on IBM Cloud, using Nvidia's HGX B300 systems, to support open-source models — IBM (IBM.N) a

hardwaretechmeme