Search: “inference”

microsoft doubles down on local ai with nvidia, but with a cost

https://preview.redd.it/uyjw2lcrvkuh1.png?width=1536&format=png&auto=webp&s=ce991be22faec3de5cbaf39119c14782b6ed0af3 link to article TLDR; new microsoft surface and nvidia rtx spark laptops are starti

local-air-localllama

10 Oct 2026

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Pay close attention to custom harnesses. This is a super interesting paper showing the impact of training inside the harness. Qwen3-14B goes…

DGX agent

Pay close attention to custom harnesses. This is a super interesting paper showing the impact of training inside the harness. Qwen3-14B goes from 22.2% to 54.8% on Spider 2.0-SQLite when it is trained

researchdair-ai--x

10 Oct 2026

A 24KB stand-alone HTML-LLM that can generate consistent stories

https://preview.redd.it/7sknv6omnguh1.png?width=1023&format=png&auto=webp&s=4aef1dc464d008b00f104519eb5399ba6132ad69 Want to try? Just go here and click 'New seed' a lot. You will get different storie

local-air-localllama

A 3D Characterization Framework for Intelligent Sequential Decision Making

arXiv:2610.11696v1 Announce Type: new Abstract: Puzzles are widely used to evaluate the reasoning capabilities of artificial intelligence (AI) systems for sequential decision making, yet approaches or

A Geometric Approach to Soft Actor-Critic with Zonotopes for Locomotion Learning

arXiv:2610.12113v1 Announce Type: cross Abstract: Off-policy actor--critic methods control overestimation bias by taking the minimum of two critics. This uses the same aggregation rule everywhere, reg

A Minimal Optical-Flow Representation for Vision-Based Tactile Rotation Classification in Robotic Manipulation Across Gravity Domains

arXiv:2610.12073v1 Announce Type: cross Abstract: Vision-based tactile sensors provide rich contact information, but processing high-resolution images can be costly for resource-constrained platforms

A Structural Theory of Cognitive Representation and Problem Solving,Contexts, Invariance, and the Knowledge Space

arXiv:2610.12306v1 Announce Type: new Abstract: Learning and problem solving depend critically on the structure of internal representations. While many modern data-driven artificial systems achieve st

researcharxiv-cs-ai

A Survey on LLM-Integrated Hardware Design Verification

arXiv:2610.10580v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly being integrated into hardware verification to automate specification interpretation, verification-artif

Acting from Belief, Looking When Needed: A Bayesian Spatial World Model for Navigation under Intermittent Perception

arXiv:2610.11591v1 Announce Type: new Abstract: Robot navigation commonly uses wide-coverage, high-frequency sensing to reduce partial observability; this reliance becomes restrictive when another tas

applicationsarxiv-cs-ro

AdaCast: Conditional Parameter Generation for Adaptive Time Series Forecasting

arXiv:2610.12240v1 Announce Type: cross Abstract: Time-series foundation models (TSFMs) have achieved strong forecasting performance across domains. However, most adaptation methods remain static. Exi

Tutorials

AgentGarten: Code Worlds for Evolving Agents

arXiv:2610.12374v1 Announce Type: new Abstract: Interactive virtual worlds allow agents to learn through exploration and interaction. What agents can learn is bounded by the environments they practice

tutorialsarxiv-cs-cv

Agentic Critical Training

arXiv:2603.08706v2 Announce Type: replace Abstract: Imitation learning (IL) teaches language-model agents to reproduce expert actions but not to distinguish them from plausible mistakes. Self-reflecti

AI Appeals Processor: A Deep Learning Approach to Automated Classification of Citizen Appeals in Government Services

arXiv:2604.03672v2 Announce Type: replace-cross Abstract: Government agencies must register, classify and route every citizen appeal within statutory time limits, and much of this work is still done b

applicationsarxiv-cs-ai

ARC: A Reasoning Recipe for Robot Foundation Models

arXiv:2610.12386v1 Announce Type: cross Abstract: The prevailing approach to improving robot foundation models (RFMs) relies on larger models, more robot demonstrations, and costly training at scale.

ASPIRE: Saddle-Point Discovery through Set Prediction and Physical Refinement

model-releasesarxiv-cs-lg

arXiv:2610.10969v1 Announce Type: new Abstract: Predicting thermally activated diffusion and defect evolution with event-driven models requires identifying atomic rearrangement mechanisms and their ac

Autoregressive Retriever: Improving Query Understanding from Item Feedback for Universal Multimodal Retrieval

arXiv:2610.11666v1 Announce Type: cross Abstract: Universal multimodal retrieval typically encodes a query once and ranks independently indexed items by embedding similarity. This design supports effi

Benchmark Designers Should 'Train on the Test Set' to Expose Exploitable Non-Visual Shortcuts

arXiv:2511.04655v2 Announce Type: replace Abstract: Multimodal LLMs can answer many questions in vision-centric benchmarks without looking at the image, using linguistic priors and skewed answer distr

Beyond Sequences: Distilling Structured Decision Memory for LLM Recommendation

arXiv:2610.11501v1 Announce Type: new Abstract: Despite the adoption of large language models (LLMs) in recommendation systems, prevailing approaches mostly model single-type behaviors (e.g., views or

researcharxiv-cs-cl

Breaking the Group Size Barrier: Parameter-Efficient Group Dance Generation with Chain-of-Dancers

arXiv:2610.11237v1 Announce Type: new Abstract: Group dance generation aims to synthesize coordinated multi-dancer choreography from music, with broad applications in animation and interactive content

Build your own harness, folks. Reading papers like this makes me realize how underexplored harness engineering really is. The authors find t…

Build your own harness, folks. Reading papers like this makes me realize how underexplored harness engineering really is. The authors find that on whole-repository migration, GPT-5.6 Sol goes from 6.5

model-releasesdair-ai--x

Tutorials

Clarify, Then Focus: Statement Normalization for Conversation Analytics at Scale

arXiv:2610.10758v1 Announce Type: cross Abstract: Enterprise conversation analytics asks many questions of millions of interactions. Each question can require reconstructing what people mean and ident

tutorialsarxiv-cs-ai

Cognition-Oriented Emotion Tracing from Causes to Consequences in Real-World Social Scenes

arXiv:2610.11410v1 Announce Type: new Abstract: Affective computing has progressed from categorical emotion recognition to open-ended affective analysis with large multimodal models. Yet affective sci

applicationsarxiv-cs-ai

Conditional Residual Prediction: Improving Autoregressive Video Diffusion without a Bidirectional Teacher

arXiv:2610.11479v1 Announce Type: cross Abstract: Causal video diffusion models generate video autoregressively, which suits streaming, interactive, and long-video generation. Under standard training,

Connected Self Forcing: Beyond Local Learning in Video Autoregression

arXiv:2610.12156v1 Announce Type: new Abstract: To stream long videos while maintaining visual quality and temporal consistency, Self Forcing mitigates exposure bias through self-rollout training on s

safetyarxiv-cs-cv

Coverage-Aware Reasoning with Medical Tokens for Diagnosis Prediction

arXiv:2610.10641v1 Announce Type: cross Abstract: Large language models (LLMs) offer promising potential for next-visit diagnosis prediction, owing to their ability to integrate longitudinal clinical

DAMP: Humanoid Locomotion via Denoised Belief Learning and Adversarial Motion Priors

arXiv:2610.11505v1 Announce Type: new Abstract: Humanoid robots possess the structural capability to traverse complex terrains. However, achieving stable t raversal without relying on perceived inform

safetyarxiv-cs-ro

DiffuPlex: Accelerating Full-Duplex Spoken Dialog Models via Rolling Masked Diffusion

arXiv:2610.12214v1 Announce Type: cross Abstract: Recent full-duplex spoken dialog models enable simultaneous listening and speaking, but fine-grained models still advance their backbone autoregressiv

researcharxiv-cs-cl

Diffusion Meta-Prompting and Steering for Generalizable Foundation Model Adaptation

arXiv:2610.11067v1 Announce Type: new Abstract: Prompt learning is a popular method for adapting foundation models, but learned prompts are typically task-specific and fail to generalize to new classe

Distilling Routed 3D Privilege for Spatial Reasoning in Vision-Language Models

arXiv:2610.12355v1 Announce Type: cross Abstract: Spatial reasoning remains a persistent weakness of vision-language models (VLMs), because RGB inputs do not directly provide geometric evidence. Exist

DPPM: Dual-Path Parametric Memory for Personalized Language Models

arXiv:2610.11776v1 Announce Type: new Abstract: Long-term personalization requires language models to use interaction history to track users' preferences across sessions. Parametric memory encodes thi

researcharxiv-cs-cl

DVD: Dynamic Vector Decoding for Efficient MLLM-based Perception

arXiv:2610.12266v1 Announce Type: cross Abstract: Multimodal large language models have made remarkable progress in bridging vision and language, facilitating various perception tasks essential for hu

local-aiarxiv-cs-ai

EchoDiST: Self-distillation-based joint learning for diffusion-conditioned echocardiographic myocardial motion estimation

arXiv:2610.11431v1 Announce Type: new Abstract: Motion estimation in echocardiography is essential for quantitative assessment of cardiac function and myocardial mechanics, but remains challenging due

safetyarxiv-cs-cv

Efficient Multi-Granularity Knowledge Transfer for Radiology Report Generation

arXiv:2610.11303v1 Announce Type: new Abstract: Radiology report generation can automatically generate clinical descriptions from X-ray images, thereby significantly improving the efficiency of radiol

Event-Centric Memory with Query-Aware Graph Augmentation for Long-Term Conversational Agents

arXiv:2610.11920v1 Announce Type: new Abstract: For persistent and personalized conversational agents, memory systems can enable them to remember, update, and reason over long histories by storing pas

local-aiarxiv-cs-cl

FearCaut-Qwen: Affective Steering in a Vision-Language Model Shifts the Decision Criterion for Hazard Assessment

arXiv:2610.11986v1 Announce Type: new Abstract: Vision-language models (VLMs) show great potential for damage assessment after a disaster, but a recurring deficiency is that they are reluctant to decl

Feature Space Adaptation for Effortless Gaussian Process Flows

arXiv:2610.11459v1 Announce Type: cross Abstract: Outside the linear-Gaussian regime, conditional sampling from Gaussian processes (GPs) is challenging. Recent methods such as FlowGP (Moss et al., (20

researcharxiv-cs-lg

FloorSAV: Elucidating Spatial Audio-Visual Context with 2D Floormap for AV-LLMs

arXiv:2610.11310v1 Announce Type: new Abstract: While 3D spatial reasoning in dynamic egocentric environments is crucial for embodied intelligence, audio-visual large language models (AV-LLMs) lack ex

From post-training to production: How TinyFish runs its web-native model on Databricks AI Runtime

**Summary** TinyFish showcases a streamlined workflow for moving their web‑native machine‑learning model from post‑training into production using Databricks AI Runtime. The article details the deploym

applicationsdatabricks

From Prompting to Composing: A Spatial Canvas Interface for Poster Generation

arXiv:2610.12230v1 Announce Type: cross Abstract: Text prompting is an indirect interface for poster generation, requiring users to encode inherently two-dimensional composition intent into a one-dime

Gated Memory: Admission-Controlled Memory Formation for Conversational AI

arXiv:2610.11270v1 Announce Type: cross Abstract: Personalized conversational AI relies on long-term memory systems that extract facts from user utterances and store them in persistent vector stores.

Generative Adversarial Loops

arXiv:2610.11458v1 Announce Type: cross Abstract: AI research progress can be viewed as the interaction between two processes: benchmark creation and method discovery. Historically, both were driven b

GUI-KV: Efficient GUI Agents via KV Cache with Spatio-Temporal Awareness

model-releasesarxiv-cs-cl

arXiv:2510.00536v2 Announce Type: replace Abstract: Graphical user interface (GUI) agents built on vision-language models have emerged as a promising approach to automate human-computer workflows. How

HarnessSQL: Harness-Native Training for SQL Agents in Realistic Database Environments

arXiv:2610.12274v1 Announce Type: new Abstract: Text-to-SQL models are commonly trained to map questions directly to static queries, whereas real-world database agents operate through stateful, multi-

applicationsarxiv-cs-cl

HENet++: Hybrid Encoding and Multi-task Learning for 3D Perception and End-to-end Autonomous Driving

arXiv:2511.07106v2 Announce Type: replace Abstract: Three-dimensional feature extraction and multi-task perception are fundamental components of modern autonomous driving systems. Although large image

Humanity's Sixth Sense: Benchmarking Intuitive Visual Reasoning in Multimodal Models

arXiv:2610.08966v2 Announce Type: replace Abstract: Humans perceive far more in a scene than what is explicitly depicted: a single glance captures past causes and future trajectories; a quick peek det

Imperative Interference: Social Register Shapes Instruction Topology in Large Language Models

arXiv:2603.25015v2 Announce Type: replace-cross Abstract: System prompt instructions that cooperate in English compete in Spanish, with the same semantic content, but opposite interaction topology. We

Improving Image-Based Nutrition Estimation Through Multimodal Food-Item Verification and Recovery

arXiv:2610.11144v1 Announce Type: cross Abstract: Single-image nutrition estimation can fail silently when visible foods are missed. Even when a food is correctly identified, its proposed region may n

researcharxiv-cs-ai

IntactWorld: Joint World Modeling with Intact Features

arXiv:2610.11174v1 Announce Type: new Abstract: While recent video generation models synthesize highly realistic visuals, they lack a genuine understanding of intrinsic real-world logic. Existing meth