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How Low Can You Go: Fine-Tuning LLMs with Bayesian Optimization (LlMBO)

arXiv:2610.18504v1 Announce Type: cross Abstract: Recently, Morris et al. introduced TinyLoRA, a strategy for LLM fine-tuning which introduces arbitrarily few parameters, and demonstrated accuracy imp

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How Shared Representations Become Specialized: Formation, Maintenance, and Latent Susceptibility

DGX agent

arXiv:2610.15830v1 Announce Type: new Abstract: When several predictions use the same internal representation, information about some targets can remain easier to recover than information about others

safetyarxiv-cs-lg

14 Oct 2026

How Tamnoon built AI-powered cloud security remediation with Amazon Bedrock

Learn how Tamnoon built Tami, an agentic cloud remediation orchestrator on Amazon Bedrock that autonomously investigates and safely remediates cloud security findings from CNAPP and cloud-native sourc

agentsaws-ml-blog

How the Classical Baseline Shapes Machine-Learning Speed Claims in Topology Optimization

arXiv:2610.16051v1 Announce Type: cross Abstract: Topology optimization places material so that a structure resists deformation under given loads. Machine-learning methods often report large speed-ups

How to Build a Benchmark That Actually Measures Taste

arXiv:2610.14707v1 Announce Type: cross Abstract: Expert-aligned 'taste' benchmarks should reward craft judgment, not the ability to game the test. We introduce TasteBench, a pairwise good-vs-bad benc

How to Train Your Latent Control Barrier Function: Smooth Safety Filtering Under Hard-to-Model Constraints

arXiv:2511.18606v2 Announce Type: replace-cross Abstract: Latent safety filters extend Hamilton-Jacobi (HJ) reachability to operate on latent state representations and dynamics learned directly from h

safetyarxiv-cs-lg

How Vision Transformers Represent Position: A Mechanistic Comparison of Absolute and Rotary Positional Encodings

arXiv:2610.13992v1 Announce Type: new Abstract: Positional embeddings encode the spatial position of each image patch in a Vision Transformer (ViT), allowing the model to distinguish different spatial

Human-Inspired Asymmetric Collaboration for Dual-Student Semi-Supervised Medical Image Segmentation

arXiv:2610.18133v1 Announce Type: new Abstract: Dual-student learning enriches predictive diversity in SSMIS by introducing a strongly augmented view alongside a weakly augmented view. Insufficient st

Hardware

Human-like autonomy emerges from self-play and a pinch of human data

arXiv:2606.19370v2 Announce Type: replace Abstract: Self-play reinforcement learning has recently emerged as a way to train driving policies without any human data. It uses cheap, large-scale simulati

hardwarearxiv-cs-lg

Human-Like Redundancy Resolution for Real-Time Bimanual Humanoid Teleoperation

model-releasesarxiv-cs-ro

arXiv:2610.16855v1 Announce Type: new Abstract: Real-time bimanual humanoid teleoperation requires accurate wrist tracking while keeping arm configurations predictable. Because a 7-DoF arm admits mult

Human Pose Estimation by Probabilistic Mixtures of Gaussian and Uniform Distributions

arXiv:2610.14093v1 Announce Type: new Abstract: Despite advancements in sub-pixel decoding, modern Human Pose Estimation (HPE) architectures remain constrained by deterministic coordinate extraction f

Humanoid Hanoi: Investigating Shared Whole-Body Control for Skill-Based Box Rearrangement

arXiv:2602.13850v4 Announce Type: replace Abstract: We introduce Humanoid Hanoi, a challenge problem for long-horizon humanoid skill composition that requires a robot to repeatedly sequence pickup, lo

researcharxiv-cs-ro

HumanPhys: A Human-Centric Physical-World Perception Benchmark for Real-World Visual Reasoning

arXiv:2610.14679v1 Announce Type: new Abstract: We introduce HumanPhys, a human-centric benchmark for real-world physical perception, and a training corpus emitted by the same pipeline. Each question

HyBRA-EEG: Hyperbolic Global-Local Brain-Region Aggregation for Self-Supervised EEG Representation Learning

arXiv:2610.16589v1 Announce Type: new Abstract: Electroencephalography (EEG) representation learning is challenged by noisy signals, inter-subject variability, and heterogeneous electrode montages in

Hybrid Context Forests and Bilateral Viterbi Matching for 3D Rib Centerline Tracing in CT

arXiv:2610.16047v1 Announce Type: cross Abstract: Automatic extraction and anatomical numbering (R01-R12, L01-L12) of all 24 rib centerlines in thoracic CT is essential for unfolded rib visualization,

Hybrid Parallel Bessel KAN Model: a Kolmogorov Arnold Network: integrated framework for developing a novel architecture to reconstruct the fused-basis approach via a parameter free quadratic interaction

arXiv:2610.17779v1 Announce Type: new Abstract: The Kolmogorov-Arnold Network (KAN) challenges traditional MLPs by placing learnable activation functions on network edges. However, scaling KANs to spa

Hybrid Reasoning Agents

arXiv:2610.18861v1 Announce Type: cross Abstract: How can we build an agent that thinks beyond human language, yet still acts through it in the external environment? Modern LLM agents still reason and

agentsarxiv-cs-lg

Local Ai

HybridDualPathNet: Cross-Fusion Attention of EfficientNetV2 and Swin Transformer for Brain MRI Classification of Alzheimer's and Parkinson's Disease

arXiv:2610.17251v1 Announce Type: new Abstract: Separating Alzheimer's Disease (AD), Parkinson's Disease (PD), and Healthy Controls (HC) using structural MRI remains challenging because disease signat

local-aiarxiv-cs-cv

HybridStitch: Pixel and Timestep Level Model Stitching for Diffusion Acceleration

arXiv:2603.07815v2 Announce Type: replace Abstract: Iterative diffusion generation requires different amounts of model capacity at different token positions. Prior model combinations allocate capacity

HYDRA: Representation Harmonized Tokenization for Multimodal Generation and Understanding

arXiv:2603.15228v3 Announce Type: replace Abstract: Unified Multimodal Models struggle to bridge the fundamental gap between the abstract representations needed for visual understanding and the detail

Hyperbolic Time Series Forecasting with Learnable Decomposition and Manifold Dynamics

arXiv:2610.15760v1 Announce Type: new Abstract: Multiscale structure is central to time series forecasting: temporal signals contain slowly varying trends, intermediate seasonal patterns, and high-fre

researcharxiv-cs-lg

I built a cheap dual 3090 rig from used parts, but why isn't it much faster?

model-releasesr-localllama

Hey everyone, I recently put together a local LLM machine using mostly second hand hardware. I wanted to experiment with local models for app development without spending a fortune on a new workstatio

Local Ai

I built an open-source dubber that keeps each actor’s own voice, fully local (OmniVoice + Whisper, 6 GB+ NVIDIA)

I've used this to watch shows and movies that have never been translated to English. There's so much great content out there, that is now accessible thanks to AI. Basically you clone the repo and tell

local-air-localllama

I built BitRun: A standalone runner for 1-bit LLMs (100–127 t/s on Apple Silicon & 40–45 t/s on PC CPUs with zero compile)

model-releasesr-localllama

I built BitRun because I wanted to run 1-bit ternary LLMs on ordinary laptops without melting my battery, spinning up a dedicated GPU, or wrestling with complex build environments. Right now, BitRun g

I really don’t understand the point of the AI slopcomments flooding my posts. At least on LinkedIn they are pushing fake expertise to make t…

I really don’t understand the point of the AI slopcomments flooding my posts. At least on LinkedIn they are pushing fake expertise to make their posters look good (it doesn’t, but whatever). But what

agentsethan-mollick--x

I trained a 15M 'decision-only' model two ways — linear recurrence vs Transformer attention. Accuracy was a coin flip; latency and training cost weren't.[R]

tutorialsr-machinelearning

Inspired by TypeSafe's Jev (a non-generative model that only outputs bounded decisions — choices, probabilities, calibrated confidence), I built two small decision models end-to-end on identical budge

I2O2I-Nav: A Benchmark with a Modular Agent for Long-Horizon Indoor-to-Outdoor-to-Indoor Navigation

model-releasesarxiv-cs-ro

arXiv:2610.18307v1 Announce Type: new Abstract: Service and delivery robots often need to complete long-horizon navigation missions spanning indoor and outdoor environments. Existing embodied navigati

I3L: Iterative Interactive Imitation Learning for Whole-Body Mobile Manipulation

arXiv:2610.17748v1 Announce Type: new Abstract: Policies trained offline from teleoperated demonstrations can degrade outside their training distribution. This gap is particularly acute in long-horizo

Tools

ICYMI from yesterday's @dealbook: inference startups are ripping as enterprises continue to adopt AI - @togethercompute's annual bookings hi…

ICYMI from yesterday's @dealbook: inference startups are ripping as enterprises continue to adopt AI - @togethercompute's annual bookings hit 1.2 billion as of July - @FireworksAI_HQ crossed 1 billion

toolstogether-ai--x

Applications

Identication and Estimation of Nonsymmetric Determinantal Point Processes

arXiv:2610.14520v1 Announce Type: cross Abstract: Determinantal point processes (DPPs) provide tractable distributions for nite random sets, but the usual symmetric-kernel specication imposes nonposit

applicationsarxiv-cs-lg

IMAGAgent: Orchestrating Multi-Turn Image Editing via Constraint-Aware Planning and Reflection

arXiv:2603.29602v2 Announce Type: replace-cross Abstract: Existing multi-turn image editing paradigms are often confined to isolated single-step execution. Due to a lack of context-awareness and close

agentsarxiv-cs-cv

Image Diffusion Models Are Good 3D Human Motion Generators

arXiv:2610.14254v1 Announce Type: new Abstract: Text-to-motion generation typically relies on dataset-specific skeletal representations, with models trained separately for benchmarks with different jo

Image Tokenizers Should Be Trained Between Images

arXiv:2610.16759v1 Announce Type: new Abstract: Latent diffusion models generate images as codes of an image tokenizer, whose decoder turns them into the pixel image. Recent tokenizers improve how wel

Images Talk Back: Guiding MMDiTs by Suppressing Image-to-Text Feedback

arXiv:2610.13941v2 Announce Type: replace Abstract: Multimodal diffusion transformers (MMDiTs) allow the evolving image to update internal text representations through joint attention. These represent

safetyarxiv-cs-cv

Imitation Learning of Avoidance Modes for Efficient Multimodal Model Predictive Control

arXiv:2610.16326v1 Announce Type: new Abstract: Multimodal model predictive control (MM-MPC) avoids local minima among moving obstacles by solving one optimal control problem (OCP) per combination of

researcharxiv-cs-ro

Imitation Learning via Discrete and Rhythmic Primitive Composition

arXiv:2610.15639v1 Announce Type: new Abstract: Long-horizon robotic manipulation is inherently composed of semantically meaningful sub-tasks. While Movement Primitives (MPs) can model these component

Imperfect Verifiers, Exact Targets: Inference-Time Scaling for Continuous Generation

arXiv:2610.15281v1 Announce Type: new Abstract: Verifier-guided inference-time scaling uses additional computation to score intermediate states and steer generation toward better outputs. However, imp

researcharxiv-cs-lg

Implicit and explicit reparameterizations of the Folded Normal and Rice distributions

arXiv:2610.17151v1 Announce Type: cross Abstract: Variational inference is a flexible tool for modeling experimental data and has proven useful in crystallography. Pathwise gradient estimators provide

researcharxiv-cs-lg

Improving dependability in robotized bolting operations

arXiv:2511.10448v2 Announce Type: replace Abstract: Bolting operations are critical in industrial assembly and in the maintenance of scientific facilities, requiring high precision and robustness to f

Improving Neural Symbolic Regression with a Diverse Prior and Post-training Alignment

arXiv:2610.17994v1 Announce Type: new Abstract: Symbolic regression is the problem of finding an expression that fits a dataset. Solving it requires searching a combinatorial space of candidate expres

safetyarxiv-cs-lg

Improving Policy Learning from Delayed Interventions

arXiv:2610.17298v1 Announce Type: new Abstract: In this work, we explore the idea of expert intervention delays in human-supervised robotic systems for imitation learning system. Previous works in imi

Improving the Evaluation of Biomedical Question Answering with Few Human Preference Signals

arXiv:2610.16008v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems are increasingly used for biomedical Question Answering (QA). However, evaluating their effectiveness rem

tutorialsarxiv-cs-lg

In-context classification: Calibration and noise in linear attention with softmax readout

arXiv:2610.17061v1 Announce Type: cross Abstract: We study in-context binary classification in a simple attention model trained to minimise a logistic loss. Each prompt has a latent logistic teacher,

In-Context Learning Can Help Vision-Language Models Overcome Training Priors

arXiv:2610.12942v2 Announce Type: replace Abstract: Vision-language models (VLMs) learn strong statistical regularities during training, which can make them fail to properly respond to visual evidence

tutorialsarxiv-cs-cv

In early 2022, the first “real” @modal user was using us for processing large scale weather data. We were anxious about going up to them and…

In early 2022, the first “real” @modal user was using us for processing large scale weather data. We were anxious about going up to them and asking them to pay ~500 for continuing to run these jobs. (

tutorialsswyx--x

In View or Out of View? A Vision-Aware Filter that Infers and Reacts to the Human's Field of View

arXiv:2610.14577v1 Announce Type: new Abstract: During human-robot interaction, sight plays an important role. When the human sees a robot, they can observe the robot's actions and better predict the

InCLAD: A Continual Learning Benchmark for Industrial Visual Anomaly Detection

arXiv:2610.15032v1 Announce Type: new Abstract: Industrial anomaly detection benchmarks have advanced rapidly, yet they remain largely static and therefore underrepresent deployment settings in which

IND-Eval: Aligning Evaluation and Simulation for Industrial Time Series Foundation Models

arXiv:2610.16652v1 Announce Type: new Abstract: We introduce IND-Eval, a public benchmark that organizes industrial time series across domains into source-specific forecasting tasks. Relative to estab