Search: “inference”

Agents are only as capable as the context they can reach. An agent with reliable access to the right information makes decisions grounded in fact; one without it guesses. And the work agents produce i

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Local Ai

🚀 Introducing MiniCPM-V 4.7, our new open-source MLLM series! Advancing the Performance–Efficiency Pareto Frontier. It brings strong multim…

DGX agent

🚀 Introducing MiniCPM-V 4.7, our new open-source MLLM series! Advancing the Performance–Efficiency Pareto Frontier. It brings strong multimodal capabilities to iOS and Android devices with extreme eff

local-aiclem-delangue--x

12 Oct 2026

Looped Diffusion Transformer: the same blocks run several times inside each denoising step, and loop depth can be changed at sampling time [R]

researchr-machinelearning

Paper: Looped Diffusion Transformer (arXiv 2609.40305, 30 Sep). Instead of making a text-to-image DiT bigger, it runs a shared group of transformer blocks several times inside each denoising step. The

PDE-PFN: Prior-Data Fitted Neural PDE Solver

arXiv:2610.13334v1 Announce Type: new Abstract: Motivated by the success of large language models (LLMs) with broad generalizability and robustness to noisy or unreliable pre-training data, we explore

PreSTO: Predictive Subtree Prefetching for Fast LLM Power Sampling

arXiv:2610.13171v1 Announce Type: new Abstract: Power sampling improves large language model (LLM) reasoning at test time by sampling from a sharpened version of the base model's distribution. Its sam

researcharxiv-cs-cl

Provenance-Aware Belief Updating in Human-AI Feedback Loops

arXiv:2610.13008v1 Announce Type: new Abstract: In repeated human-AI interaction, a single observation can be quoted, summarized, and returned to a model as multiple reports, making repetition look li

REDaCT: Collapse-Free Unlearning in Large Reasoning Models

arXiv:2610.12769v1 Announce Type: cross Abstract: Unlearning in large reasoning models (LRMs) requires removing forget-set information from both the reasoning trace and the final answer. Existing appr

Reflect-VLA: Internalizing Reflective Guidance via Dual-Path On-Policy Self-Distillation for Autonomous Driving

arXiv:2610.13453v1 Announce Type: new Abstract: Reinforcement Learning (RL) substantially improves planning performance in autonomous-driving Vision-Language-Action (VLA) models. However, existing RL

safetyarxiv-cs-ro

ReplaySSM: Rethinking State Storage for Faster Hybrid-Model Decoding

model-releasesnvidia-developer

ReplaySSM stores an SSM state as a high‑precision checkpoint plus a buffer of recent inputs, cutting memory traffic by ~50 % and accelerating SSM decoding kernels on NVIDIA Blackwell Ultra B300 GPUs b

Hardware

SBNO : Schrodinger Bridge Neural Operator for the Forward and Inverse Problems under Missing Information

arXiv:2610.13317v1 Announce Type: new Abstract: Partial differential equation (PDE) surrogate modeling often relies on either dense observations or access to governing equations/physics constraints. I

hardwarearxiv-cs-lg

Self-Compacting Language Model Agents

model-releasesapple-ml-research

Long agent traces composed of chains of thought and tool calls accumulate stale content that anchor subsequent generations, and eventually outgrow the context window. Existing scaffolds mitigate it wi

Self-Preservation in Language Models

arXiv:2610.12602v1 Announce Type: cross Abstract: Continual learning (CL) seeks to adapt pretrained models while preserving prior capabilities. Yet the tasks supplied for preservation cover only part

SpireBench: Evaluating Long-Horizon Strategic Play of Agentic Models with Slay the Spire

arXiv:2610.12596v1 Announce Type: new Abstract: Agentic large language models now tackle complex tasks, yet strategic reasoning over long horizons is under-studied: most agentic benchmarks are short a

Target-Constrained Pooling for Trajectory Extrapolation

arXiv:2610.13034v1 Announce Type: new Abstract: Trajectory extrapolation from a partial target trajectory is underdetermined, but completed related trajectories provide information about the unresolve

Test-Time Memory Construction

arXiv:2610.13348v1 Announce Type: new Abstract: Large Language Models (LLMs) struggle to answer questions over long interaction histories, where relevant evidence may be scattered across distant sessi

researcharxiv-cs-cl

Agents

This is how we built the filesystem behind Perplexity Projects as a Git forge for agents. Each agent works in its own sandbox and commits to…

This is how we built the filesystem behind Perplexity Projects as a Git forge for agents. Each agent works in its own sandbox and commits to a shared repository where people and other agents can build

agentsperplexity--x

UniConFlow: A Unified Constrained Flow-Matching Framework for Certified Motion Planning

arXiv:2506.02955v3 Announce Type: replace-cross Abstract: Generative models have become increasingly powerful tools for robot motion generation, enabling flexible and multimodal trajectory generation

safetyarxiv-cs-ai

Local Ai

User Trajectory Prediction Unifying Global and Local Temporal Information

arXiv:2508.02161v2 Announce Type: replace Abstract: Trajectory prediction is essential for formulating proactive strategies that anticipate user mobility and support advance preparation. Therefore, ho

local-aiarxiv-cs-lg

Verifiable Sampling for Delegated Generative Quantum Machine Learning

arXiv:2610.13211v1 Announce Type: cross Abstract: Generative machine learning has shown remarkable results across a wide range of interdisciplinary tasks, motivating significant efforts toward Quantum

When MLLMs miss what humans read: diagnosing and learning to read squint text

arXiv:2610.13465v1 Announce Type: cross Abstract: Multimodal LLMs can fail to read text embedded in an image's coarse structure (text a human recovers by squinting) and report that no text is present.

safetyarxiv-cs-ai

A Little Help Please?

https://preview.redd.it/9k5fw4j47puh1.png?width=545&format=png&auto=webp&s=ff0a6ff6fb69ae9a9bcd579bd612c553fc3e2a00 https://preview.redd.it/xcwzlmo77puh1.png?width=664&format=png&auto=webp&s=c8a637e2e

model-releasesr-ollama

10 Oct 2026

Industry

What to expect during the AI Data Pipeline Forum: Join theCUBE Oct. 13

The artificial intelligence infrastructure race is no longer just about building faster chips. AI infrastructure bottlenecks are shifting attention to a bigger challenge: keeping those chips supplied

industrysiliconangle

10 Oct 2026

A Unified Score Matching Paradigm for Video Anomaly Detection and Anticipation

model-releasesarxiv-cs-cv

arXiv:2610.11149v1 Announce Type: new Abstract: Video anomaly detection (VAD) is a fundamental and safety-critical task in computer vision. Recent generative approaches detect anomalies from a distrib

Ai2 at COLM 2026: Open research, from models to agents for science

Ai2 joined COLM 2026 to share advances in open language models, training infrastructure, and AI for science, including Olmo Hybrid, Asta, and Bolmo, while connecting with the broader research communit

researchai2

Local Ai

AtomWorld-Mirror: Macro-Step World Modeling of Critical Evolution Backbones for Materials Dynamics

arXiv:2610.11527v1 Announce Type: new Abstract: Atomistic simulation is a fundamental tool for studying long-term materials evolution, from diffusion and defect dynamics to interfacial reactions and f

local-aiarxiv-cs-ai

BudgetPix: Compute-Adaptive Tokenization for Pixel-Space Image Diffusion

arXiv:2610.12307v1 Announce Type: new Abstract: Most image generation models rely on uniform tokenization, allocating the exact same computational budget to equally-sized image patches. This static pa

researcharxiv-cs-cv

Bullish on this trend of making post-training more accessible. A new post-training era is upon us. If you work on agentic RL, long-context t…

Bullish on this trend of making post-training more accessible. A new post-training era is upon us. If you work on agentic RL, long-context tasks (a big focus today) are expensive, inefficient, and don

model-releasesdair-ai--x

C-LoRA: Continual Low-Rank Adaptation for Pre-trained Visual Models

model-releasesarxiv-cs-lg

arXiv:2502.17920v2 Announce Type: replace Abstract: Pre-trained visual models have become fundamental in computer vision, but they face challenges in continual learning scenarios where data and tasks

CAPABLE: Capability-Aware Policy Adaptation via Behavioral Latent Encoding

model-releasesarxiv-cs-lg

arXiv:2610.11971v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies assume the embodiment on which they were trained and can fail when a joint fault changes how commanded actions a

Compile the Table: Query-Calibrated Operator Compression for Tabular In-Context Learning

arXiv:2610.11784v1 Announce Type: new Abstract: Tabular in-context learning (ICL) has emerged as a training-free and accurate paradigm for tabular prediction, but current approaches to compressing its

Density Ratio Estimation with Stein Displacement Fields

arXiv:2610.12437v1 Announce Type: cross Abstract: Density ratios quantify distribution shift from a probability-mass point of view, whereas displacement fields describe, from a dynamical point of view

From Suppression to Repair: Mitigating Object Hallucination in Large Vision-Language Models via Localized Distribution Alignment

arXiv:2610.11826v1 Announce Type: cross Abstract: Object hallucination remains a major obstacle for large vision-language models (LVLMs) to generate reliable content. An intuitive mitigation strategy

Applications

ISBO: Scalable Spatio-Temporal Bayesian Optimization with Log Gaussian Cox Process Models via the INLA-SPDE Approach

arXiv:2610.12213v1 Announce Type: cross Abstract: Bayesian Optimization (BO) is a popular method for efficiently optimizing expensive black-box objectives. However, BO utilizing standard Gaussian Proc

applicationsarxiv-cs-lg

Learning to Orchestrate Evolutionary Search: Progression-Aware Deep Reinforcement Learning for Dynamic DE-CMA-ES Coordination in Optimization and Structural Model Updating

arXiv:2610.11546v1 Announce Type: cross Abstract: Solving high-dimensional structural model updating problems requires an algorithm capable of navigating complex, non-convex landscapes with correlated

LTBD: Learnable Trust-Boundary Delimiters for Prompt Injection Defense

arXiv:2610.11634v1 Announce Type: cross Abstract: Large language models (LLMs) perform remarkably well on complex tasks, yet remain highly vulnerable to prompt injection attacks, where malicious instr

Machine Learning Meets High-Energy Nuclear Physics: From Pattern Recognition to Physics-Integrated Discovery

arXiv:2610.12293v1 Announce Type: cross Abstract: Machine learning (ML) in high-energy nuclear physics (HENP) is entering a new stage in which physical knowledge is incorporated more directly into dat

Multimodal Graph Retrieval-Augmented Sequential Recommendation via Collaborative Filtering Paths

model-releasesarxiv-cs-lg

arXiv:2610.11228v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong potential for sequential recommendation through their ability to reason over complex m

Nullify: Null-Space Activation Steering for Training-Free LLM Unlearning

arXiv:2610.10655v1 Announce Type: cross Abstract: Large Language Models (LLMs) inevitably internalize substantial amounts of sensitive or private information during pre-training, while LLM unlearning

Opera: A Verbal Critic Framework for Long-horizon Coding Agents

arXiv:2609.33987v2 Announce Type: replace Abstract: Long-horizon coding agents need timely corrections, yet feedback can be ineffective or even harmful when it misjudges ongoing work or fails to addre

safetyarxiv-cs-cl

Local Ai

Point-Focused Attention Meets Context-Scan State Space: Robust Biological Visual Perception for Point Cloud Representation

arXiv:2610.11342v1 Announce Type: new Abstract: Synergistically capturing intricate local structures and global contextual dependencies has become a critical challenge in point cloud representation le

local-aiarxiv-cs-cv

RT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Models

model-releasesarxiv-cs-cv

arXiv:2510.25257v2 Announce Type: replace Abstract: Real-time object detection has achieved substantial progress through meticulously designed architectures and optimization strategies. However, the p

SLVR: Structured Latent Visual Reasoning via Human-like Reasoning Flows

arXiv:2610.10563v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) often answer visual reasoning questions by relying on linguistic priors rather than task-relevant visual evid

SpaceCast-Bench: Evaluating Predictive Spatial Reasoning in Vision-Language Models

model-releasesarxiv-cs-cl

arXiv:2610.12402v1 Announce Type: cross Abstract: Existing spatial reasoning benchmarks mainly test spatial perception: reading off relations already visible in the input. Yet real-world spatial intel

SV-TAD: Native Sparse Convs for Efficient Temporal Action Detection

model-releasesarxiv-cs-cv

arXiv:2610.11579v1 Announce Type: new Abstract: To adapt billion-parameter Vision Transformers for long-video understanding, recent methods freeze the backbone and train lightweight convolutional modu

TAM: Task-Aware Memory Distillation for Efficient Spatiotemporal Prediction

arXiv:2610.11617v1 Announce Type: cross Abstract: Knowledge distillation enables efficient spatiotemporal prediction by transferring knowledge from an accurate teacher to a compact student. However, m

Hardware

The Operator Mismatch Problem: Deploying BEV Perception with Portable GPU Compute

arXiv:2610.11504v1 Announce Type: new Abstract: Modern autonomous driving systems rely on bird's-eye-view (BEV) perception models that fuse camera and LiDAR inputs to detect objects in 3D space. These

hardwarearxiv-cs-ai

UltraLight Luma: A Novel Edge-Deployable Perception Network for Crop-Row Segmentation in Agricultural Robotics

model-releasesarxiv-cs-ro

arXiv:2610.11764v1 Announce Type: new Abstract: Reliable crop-row perception is essential for autonomous agricultural robots, but low-cost deployment is constrained by computation, memory, power, and

When Lower Reconstruction Loss Hurts: Distributionally Robust Refinement for Low-Bit LLM Quantization

arXiv:2610.11226v1 Announce Type: new Abstract: Weight-only post-training quantization (PTQ) relies heavily on reconstruction loss minimization to preserve model quality at low precision. We show that