Search: “inference”

Using Line Segment Tracking to enable ML-based Track Reconstruction in CMS

arXiv:2610.15963v1 Announce Type: cross Abstract: High-pileup conditions in CMS during the HL-LHC era make charged-particle tracking increasingly challenging as detector occupancy and combinatorics gr

local-aiarxiv-cs-lg

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Model Releases

VRIQ: Benchmarking and Diagnosing the Visual-Reasoning IQ of Vision-Language Models

DGX agent

arXiv:2602.05382v2 Announce Type: replace Abstract: Vision-language model (VLM) errors on visual reasoning may come from missing visual structure, from mistakes after that structure is extracted, or f

model-releasesarxiv-cs-cv

14 Oct 2026

Walk Like This: Stylized Locomotion for Physics-Based Characters through Example-Driven Diffusion

arXiv:2610.18147v1 Announce Type: new Abstract: We present a real-time framework for expressive legged locomotion that enables independent control over velocity and style. Unlike existing data-driven

researcharxiv-cs-ro

Tutorials

WAVE-0: Bridging VLA Policies and WAMs with Lightweight Latent Future Prediction

arXiv:2610.18568v1 Announce Type: new Abstract: Vision-language-action (VLA) policies excel at generalist robotic manipulation but generate actions without explicitly modeling their environmental cons

tutorialsarxiv-cs-ro

What Can Language Models Inherit from Solomonoff Induction? Limits, Attainable Properties, and What Served Conditionals Reveal

arXiv:2610.14007v1 Announce Type: new Abstract: A familiar line of reasoning runs as follows: language models are flexible approximators trained under a strictly proper loss, so scale brings them clos

When Repeated Measurements Hurt Tabular Foundation Models

arXiv:2610.16801v1 Announce Type: cross Abstract: Tabular foundation models (TFMs) achieve state-of-the-art performance on IID benchmarks, but how do they respond to repeated measurements at the same

researcharxiv-cs-lg

Agents

World2TS: Real-World Event Context for Time-Series Forecasting

arXiv:2610.14861v1 Announce Type: new Abstract: Time-series forecasting plays a vital role in a wide range of real-world applications. Recent approaches have achieved strong performance by modeling te

agentsarxiv-cs-lg

WUSPruner: Second-Moment-Optimal Transforms for Structured Pruning

arXiv:2610.15394v1 Announce Type: new Abstract: Structured pruning is typically formulated as identifying which model dimensions to remove, often within the model's original representation. However, t

A gap that has been fixed in our methodology that highlighted a decline was not including local models (GGUF, AWQ, ONNX, etc). Earlier, thes…

A gap that has been fixed in our methodology that highlighted a decline was not including local models (GGUF, AWQ, ONNX, etc). Earlier, these were far harder to track and closer to a rounding error. N

local-aiclem-delangue--x

David Silver is one of the all-time greats. He was the creator of AlphaGo, which changed the course of history by showing that neural nets c…

David Silver is one of the all-time greats. He was the creator of AlphaGo, which changed the course of history by showing that neural nets could achieve superhuman performance for the first time. He a

safetysonya-huang--x

Gausify Orbit is now open source: turn AI-generated 360 orbit videos into Gaussian Splats, entirely in your browser

model-releasesr-stablediffusion

A few days ago I posted “Gausify Orbit - I am building a web application to transform images into Gaussian Splats”, and it was removed because the project wasn’t open source yet. It’s now released und

How far are we from a local model being able to optimize it's own runtime stack?

model-releasesr-localllama

A lot of projects have come up recently consisting of specific hardware config specialized forks of existing conferencing engines, but they all seem to be made using Claude or OpenAI's biggest frontie

I built a pytorch library of pretrained models for 3D point clouds following timm standards [P]

model-releasesr-machinelearning

https://preview.redd.it/m5e9anluo8vh1.png?width=1080&format=png&auto=webp&s=4c80687e6fe40036843a97ed8975ce46eaab0662 I am excited to share a project I have been working on during the past few years du

LiquidAI/LFM2.5-24B-A2B

model-releasesr-localllama

Gguf's: https://huggingface.co/LiquidAI/LFM2.5-24B-A2B-GGUF Free Demo: https://playground.liquid.ai 'LFM2.5-24B-A2B is a 24B-parameter reasoning model with only 2B active parameters, built for fast, p

Mac mini for running LLMs and AI agents 24/7: Prioritize RAM or CPU/GPU performance?

I’m planning to get a Mac mini mainly to run local LLMs and AI agents 24/7. I plan to run models up to 27B parameters with Q4 quantization, and maybe not for coding, maybe just for everday task and mo

local-air-localllama

Mac users: Fast and Easy image/video/audio generation workflows, finally!

local-air-stablediffusion

One of the frustrating things about local AI generation on Mac is getting different models and tools to work together smoothly and fast. Valtz is a new native macOS app powered by Vpipe, a high-perfor

Hardware

NVIDIA Run:ai Is Now Open Source as Part of NVIDIA DSX AI Factory Platform

On October 13, 2026 NVIDIA released the complete Run:ai platform—an AI workload and GPU orchestration system—as open‑source software under its DSX AI Factory Platform. The modular release includes fou

hardwarenvidia-developer

VigenFlow: FLUX.1-schnell, FLUX.2-klein-4B and Z-Image-Turbo running locally on the AMD Ryzen AI NPU, no discrete GPU needed (Windows + Ubuntu)

local-air-stablediffusion

Hi all, I'm the developer of VigenFlow, a local image generation and editing server that runs diffusion models on the AMD Ryzen AI NPU (XDNA 2) + CPU. If you have a Ryzen AI laptop or mini PC without

Applications

wait so this feels a bit different too in a good way

applicationsyohei-nakajima--x

wait so this feels a bit different too in a good way You already gave the LLM the answer. So why is it writing it out from scratch? Introducing a new AI model architecture: Constrained Decoding Models

Weird blog post from OrcaRouter

model-releasesr-localllama

I came across this blog post from OrcaRouter: https://www.orcarouter.ai/blog/qwen-3-8-next-vs-qwen-3-8 Not only is the blog post nonsensical in some parts, it's also completely without any value. It b

A Categorical Atlas of Parameter-Efficient Fine-Tuning: Cones, Orbits, and Gauges

arXiv:2610.12728v1 Announce Type: new Abstract: Parameter-efficient fine-tuning has hundreds of methods, usually compared by parameter count and benchmark score. We compare them as maps. A pretrained

A Sampling Complexity-aware Framework for Discrete-time Fractional-Order Dynamical System Identification

arXiv:2501.17499v1 Announce Type: cross Abstract: A variety of complex biological, natural and man-made systems exhibit non-Markovian dynamics that can be modeled through fractional order differential

Adaptive DHiSparse: Speculative Decoding over a Load-Adaptive KV Hierarchy

arXiv:2610.13708v1 Announce Type: new Abstract: Long-context serving runs out of KV memory before the hardware reaches its useful throughput. HiSparse stores history in host memory and fetches only th

Agreement Without Alignment: Label-Free Rubric Clarification Increases LLM-Judge Consensus but Not Agreement with Humans

arXiv:2610.13303v1 Announce Type: cross Abstract: LLM judges are increasingly deployed as panels, and disagreement among panel members is often read as a symptom of an unclear rubric. We test a label-

safetyarxiv-cs-ai

Algebraic Integer Quantization for Machine Learning Applications

arXiv:2610.12494v1 Announce Type: new Abstract: In this article, we propose algebraic integer number formats (AINF) as a framework for highly configurable and accurate compressed computation. A key pr

An Input-Dependent Readout Phase for Resonant Sequence Models

model-releasesarxiv-cs-cl

arXiv:2610.12496v1 Announce Type: cross Abstract: Sequence models with a fixed-size state avoid the quadratic cost of attention, but face a design choice. An input-dependent state transition gives con

Approximation of differential entropy in Bayesian optimal experimental design

arXiv:2510.00734v2 Announce Type: replace-cross Abstract: Bayesian optimal experimental design provides a principled framework for selecting experimental configurations that maximize obtained informat

researcharxiv-cs-lg

AutoIndexer: Flexible-Order Decoding by Training Causal Models on Chains of Edits

arXiv:2610.12545v1 Announce Type: cross Abstract: Autoregressive decoding is less suited to non-causally ordered data, e.g., cross-references or future dependencies, since their outputs cannot be revi

Cancerous Backdoor Attack: Gradual Activation via Invisible Tokens and A Stage Controller

arXiv:2610.12644v1 Announce Type: cross Abstract: Backdoor Attacks on Large Language Models (LLMs) typically follow a trigger-response pattern, where satisfying a trigger condition activates a single

Agents

CB-Orchestrator: Adaptive Workflow Optimization for LLM Agents via Contextual Bandits

arXiv:2610.13064v1 Announce Type: new Abstract: Large Language Model (LLM) agents have demonstrated remarkable capabilities in tackling complex tasks through agentic workflows. However, manually desig

agentsarxiv-cs-lg

CLEAT: Learning Value-Guided Clarification for Interactive Agents

arXiv:2610.12655v1 Announce Type: new Abstract: LLM agents can execute increasingly complex tasks, but effective assistance also requires aligning their actions with goals and constraints that users m

safetyarxiv-cs-ai

Collaborative Learning and Reasoning over Model Slices

arXiv:2610.12927v1 Announce Type: new Abstract: Large language models (LLMs) excel across diverse tasks, benefiting from knowledge priors, in-context reasoning, and test-time computation. Despite thes

Agents

Competence-Aware Orchestration for LLM-Based Multi-Agent Systems

arXiv:2610.13144v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have emerged as a promising paradigm for enhancing complex reasoning through role specialization and collaboration,

agentsarxiv-cs-ai

CopRoute: Dependence-Aware Conformal Routing for Language Models

arXiv:2610.13276v1 Announce Type: new Abstract: Set-based language model routing aims to increase the coverage of the event where at least one model answers a query correctly while controlling the num

safetyarxiv-cs-lg

CRM: Retrieval Model with Controllable Condition

arXiv:2412.13844v2 Announce Type: replace-cross Abstract: Retrieval models for recommendation need to account for outcomes such as watch time while searching large item corpora efficiently. We present

Data-driven Optimal Sensor Placement for Aerosol Monitoring in the UK

arXiv:2610.12658v1 Announce Type: new Abstract: We develop a data-driven sensor-placement framework and apply it to aerosol monitoring in the United Kingdom (UK). A trained convolutional Gaussian neur

DEAF: A Benchmark for Diagnostic Evaluation of Acoustic Faithfulness in Audio Language Models

arXiv:2603.18048v3 Announce Type: replace Abstract: Recent Audio Multimodal Large Language Models (Audio MLLMs) demonstrate impressive performance on speech benchmarks, yet it remains unclear whether

Applications

Discovering Phase Space Structure in Learned Hamiltonian Systems

arXiv:2509.23003v3 Announce Type: replace-cross Abstract: Mechanics-inspired neural dynamical models improve interpretability and physical consistency, but they usually assume a known configuration sp

applicationsarxiv-cs-ai

Energy-Efficient Spiking Neural Networks for Sensing-Aided Beam Prediction

arXiv:2610.12507v1 Announce Type: cross Abstract: Sensing-aided beam prediction can reduce the beam-training overhead of millimeter-wave (mmWave) systems by leveraging environmental information from c

Applications

Enhancing Legal Reasoning in Pre-trained Language Models via Knowledge Graph-Guided Multi-Task Pre-training

arXiv:2610.13722v1 Announce Type: new Abstract: Legal language understanding requires reasoning over semi-structured regulatory documents, yet standard pre-training objectives do not explicitly target

applicationsarxiv-cs-cl

Equal-Budget Monte Carlo Tree Search versus Randomized-Restart List Scheduling for DAG Workflows: A Controlled Equal-Budget Computational Study

arXiv:2610.12542v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) is often proposed for scheduling directed-acyclic-graph (DAG) workflows, yet most studies never run the comparison that c

Evo-World: A Lightweight Vision-Language-Action Model with Future Motion Prediction via Optical-Flow Supervision

arXiv:2610.12936v1 Announce Type: new Abstract: Vision-language-action (VLA) models provide a unified framework for visual understanding, language grounding, and robot control, yet anticipating how th

safetyarxiv-cs-ro

Exploring Attention Sinks in Text-to-Image Transformers from Diffusion and Autoregressive Models

arXiv:2610.13337v1 Announce Type: cross Abstract: Attention sinks are tokens or positions that consistently receive disproportionate attention mass, often beyond what their semantic content would sugg

local-aiarxiv-cs-cl

From Impact to Insight: Dynamics-Aware Proprioceptive Terrain Sensing on Granular Media

arXiv:2604.02563v2 Announce Type: replace Abstract: Robots that traverse natural terrain must interpret contact forces generated under highly dynamic conditions. However, most terrain characterization

researcharxiv-cs-ro

GeoFitBench-LLM: A Benchmark for Assessing Large Language Models' Capabilities in Geospatial Data Requirements Elicitation for Geo-Analytic Tasks

arXiv:2610.12669v1 Announce Type: cross Abstract: Large language models are becoming central to GeoAI systems, yet their evaluation rarely considers the elicitation of geospatial data requirements. Th

GIST: Generator-state-Informed Supervision for Tabular Foundation Models

arXiv:2610.12904v1 Announce Type: new Abstract: Tabular foundation models (TFMs) based on prior-data fitted networks typically use sampled hard query labels, leaving avoidable sampling variability in

researcharxiv-cs-lg

Humanize Olympiad Agents: A Multi-Session Workflow for Olympiad Problem Solving with Solve, Review, Wiki, Verify

arXiv:2610.13632v1 Announce Type: new Abstract: Large language model (LLM) agents are rapidly improving on long-horizon scientific and olympiad tasks. Recent systems have produced a Lean-formalized re

Knowing When to Stop: Efficient Context Processing via Latent Sufficiency Signals

model-releasesarxiv-cs-cl

arXiv:2502.01025v4 Announce Type: replace Abstract: Large language models (LLMs) process entire input contexts indiscriminately, which is inefficient when the information required to answer a query is