Search: “inference”

Mutual Information Constrained Chernoff Bottleneck

arXiv:2609.37994v1 Announce Type: cross Abstract: The classical information bottleneck (IB) measures the relevance of a representation U of X to a target Y by I(U;Y), which does not directly character

MVG-WAM: Multiple View Geometry-Aware World-Action Modeling for Robotic Manipulation

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arXiv:2609.37793v1 Announce Type: new Abstract: World-Action Models (WAMs) couple visual dynamics with action prediction, bringing the rich priors of pretrained video models to robotic manipulation. H

local-aiarxiv-cs-ro

30 Sept 2026

MyoCodec: A Streaming Neural Codec for Electromyography

arXiv:2609.36687v1 Announce Type: cross Abstract: Neural codecs encode continuous signals into compact sequences of discrete tokens, providing an interface for efficient transmission, storage, and tok

NeuronEye: Query-Guided Visual Concept Activation for Vision-Language Reasoning

arXiv:2609.38098v1 Announce Type: new Abstract: Current vision-language models (VLMs) encode visual information in dense hidden states where object identity, spatial layout, and local attributes are i

local-aiarxiv-cs-ai

Neurosymbolic Routing for Reliable Reasoning on Resource-Constrained Edge Devices

arXiv:2609.35833v1 Announce Type: new Abstract: Running a language model on edge hardware provides private and low-latency reasoning without a network connection, and yet the small models that fit on

hardwarearxiv-cs-ai

OmniRoute: Mapping Temporal Semantic Evidence to Audio-Visual Token Budgets for Efficient Omnimodal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2609.37052v1 Announce Type: new Abstract: Omnimodal large language models (Omni-LLMs) encode audio and visual streams into temporally interleaved token sequences for multimodal reasoning. Howeve

OmniVCBench: Benchmarking Evidence-Grounded Multimodal Reasoning Towards AI Virtual Cells

arXiv:2609.37773v1 Announce Type: new Abstract: Artificial Intelligence Virtual Cells (AIVCs) are envisioned as scientific agents that simulate cellular responses, explain underlying mechanisms, and s

On Calibration of Large Language Models: From Response To Capability

arXiv:2602.13540v2 Announce Type: replace-cross Abstract: Accurate confidence estimation is critical for reliable use of large language models (LLMs). Prior work on LLM calibration largely focuses on

On-demand GPU infrastructure startup GMI Cloud raises $263M to fuel global expansion

Taiwan-based neocloud GMI Cloud Inc. wants to capitalize on what it says is an “unprecedented” demand for artificial intelligence computing power after raising a massive 663 million in funding from tw

hardwaresiliconangle

OpenAI's New Agent Stack: Superhuman Computer Use, Dots, Decisions API, UltraFast, & the AI Cloud https://www.latent.space/p/devday-2026 @Op…

OpenAI's New Agent Stack: Superhuman Computer Use, Dots, Decisions API, UltraFast, & the AI Cloud https://www.latent.space/p/devday-2026 @OpenAI’s @AriX and @nikunjhanda explain why Computer Use is al

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OTT3R: Multi-View 3D Reconstruction and Fast Dataset Generation at 1% Compute

model-releasesarxiv-cs-cv

arXiv:2609.36374v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models have achieved impressive performance by scaling model and dataset size, but their cost excludes most research grou

PDE-OBS: Controlled Evaluation Across Observation Patterns

arXiv:2609.36521v2 Announce Type: new Abstract: Physical-field reconstruction and forecasting depend on both measurement density and spatial layout, yet evaluation under a single observation pattern d

PHASE: Multi-Regime Modeling of Incompressible Magnetohydrodynamics

arXiv:2609.37609v1 Announce Type: new Abstract: Magnetohydrodynamics (MHD) is central to plasma modeling in astrophysics, space science, fusion, and engineering, but resolving multiscale MHD dynamics

PhysWAM: Physically Consistent World Action Model for Autonomous Driving

arXiv:2609.37970v1 Announce Type: cross Abstract: World-action models (WAMs) jointly predict how a scene will evolve and how an agent should act, however joint generation alone does not necessarily im

agentsarxiv-cs-cv

Pixels to Keys: Exploring Spatial and Motion Cues in Gameplay Inverse Dynamics

arXiv:2609.37907v1 Announce Type: new Abstract: Video games offer scalable environments for studying perception and control in embodied agents.Abundant online gameplay videos could supply demonstratio

Pow3R-SLAM: Real-Time RGB-D SLAM with 3D Reconstruction Priors

arXiv:2609.38054v1 Announce Type: cross Abstract: We present Pow3R-SLAM, a real-time RGB-D simultaneous localization and mapping (SLAM) system that uses Pow3R for tracking and mapping. Inspired by MAS

researcharxiv-cs-cv

PR-OPD: Privileged Representation On-policy Self-Distillation for Agentic Reinforcement Learning

arXiv:2609.36642v1 Announce Type: new Abstract: Language-model agents are usually trained by reinforcement learning from one reward per episode, and privileged self-distillation enriches it by letting

safetyarxiv-cs-lg

Preconditioned Physics-Informed Neural Operator Training

arXiv:2609.36216v1 Announce Type: new Abstract: Neural operators are typically trained in a supervised fashion, which requires a dataset to be generated with a classical solver. Training them physics-

PreferenceFlow: Test-Time Guidance of Flow-Matching Robot Policies from Human Interventions

arXiv:2609.36872v1 Announce Type: new Abstract: Flow-matching policies can represent complex robot behaviors but remain susceptible to local errors under distribution shift at deployment. Many reinfor

local-aiarxiv-cs-ro

Tutorials

Pretraining Latent Information Feedback Transformers with Teacher Supervision

arXiv:2609.38149v1 Announce Type: new Abstract: Transformer language models (LMs) are feed-forward: deep-layer representations are never fed back to shallower layers, and the only pathway for informat

tutorialsarxiv-cs-cl

Principled Thoughts for Latent Recursive LLM Systems

arXiv:2609.36159v1 Announce Type: new Abstract: Large language models can reason in continuous space instead of decoded text, by recurring on their own hidden states or by passing those states between

agentsarxiv-cs-ai

Probability Contracts: Accuracy, Coherence, and Decisions Across LLM Interfaces

arXiv:2609.37470v1 Announce Type: new Abstract: A probability used for a decision should refer to the same event across equivalent requests. We introduce probability contracts, a benchmark connecting

Probe-Space Preconditioning for Fast and Stable Zero-Order Training

arXiv:2609.38095v1 Announce Type: new Abstract: Backpropagation (BP) dominates deep learning but imposes a massive memory tax. For example, training OPT-30B with Adam requires approx 600GB of GPU memo

hardwarearxiv-cs-lg

RareDx: Controlled Knowledge Integration and Graph-Grounded Policy Optimization for Rare-Disease Diagnosis

arXiv:2609.35549v2 Announce Type: replace Abstract: Rare-disease diagnosis is a long-tail reasoning problem: phenotypes are incomplete, individual disorders are sparsely documented, and relevant evide

ReCaVSR: One-Step Streaming Diffusion Video Super-Resolution with Recycled Latents and Learned Cache Routing

arXiv:2609.37831v1 Announce Type: new Abstract: Real-time diffusion-based video super-resolution (VSR) is in high demand for online streaming, yet stringent latency requirements often compromise gener

local-aiarxiv-cs-cv

Reference-Guided Machine Unlearning

arXiv:2603.11210v2 Announce Type: replace Abstract: Machine unlearning aims to remove the influence of specific training data from a model while preserving its general utility. In vision, many approxi

Regime Boundary Alignment for Evidence-Gated Question Answering

arXiv:2609.37491v1 Announce Type: cross Abstract: Retrieval-augmented language models are expected to answer from the retrieved evidence, but in practice they often keep answering when that evidence i

safetyarxiv-cs-ai

ReMem: Rethinking Perception and Memory in Long-Context Recommendation Agents

arXiv:2609.37311v1 Announce Type: new Abstract: Recent Recommendation Agents (RecAgents) offer a promising alternative by shifting recommendation to an active, user-side paradigm, where generative age

agentsarxiv-cs-ai

Rethinking Soft Tokens for Parallel Decoding in Diffusion Language Models

arXiv:2609.37391v1 Announce Type: new Abstract: Diffusion language models (DLMs) enable parallel generation by predicting and committing multiple tokens at each denoising step, yet they can generate i

S^3: Spectral Null-Space Swap Makes Reasoning Models Efficient

arXiv:2609.37976v1 Announce Type: cross Abstract: LLMs trained with Chain-of-thought excel in reasoning capability, but often come with excessive token cost. We find that the core of reasoning capacit

Scaling Video Generation for Reasoning: At What Cost?

arXiv:2609.36599v1 Announce Type: cross Abstract: We study whether scaling video generation enables models to reason about hidden information from the past frames, and at what computational cost. Our

Scaling Zero-Order Pretraining through Model Sharding

arXiv:2609.37899v1 Announce Type: new Abstract: Zero-order optimization (ZO) trains without backpropagation, making it relevant to forward-only hardware and non-differentiable loss, but its gradient v

hardwarearxiv-cs-lg

Scene-Consistent Illumination Transfer for Inserted Advertising Graphics

arXiv:2609.37951v1 Announce Type: new Abstract: Replacing a visible advertisement in a broadcast frame is geometrically straightforward but photometrically delicate. A pasted graphic can have the corr

Scouting the Dynamics Gap: Test-Time Policy Adaptation via Action-Outcome Feedback

arXiv:2609.36107v1 Announce Type: new Abstract: While pretrained robotic policies exhibit impressive capabilities in controlled environments, unobserved physical properties and dynamics require these

safetyarxiv-cs-ro

Screening Is Enough

arXiv:2604.01178v4 Announce Type: replace-cross Abstract: We call query--key relevance absolute when its values lie on a fixed bounded scale, depend on neither competing keys nor sequence length, requ

Seg3DParts: Segmentation-Grounded Controllable Part-Level 3D Generation

arXiv:2609.36918v1 Announce Type: new Abstract: Part-level 3D assets are essential for editing, reassembly, and interaction, yet recovering such structure from a single image remains challenging due t

safetyarxiv-cs-cv

Selective Elicitation as a Commercial Influence Channel: A Reproducible Synthetic Shopping-Agent Stress Test

arXiv:2609.36614v1 Announce Type: new Abstract: A commercial incentive need not enter the final ranking algorithm to affect a shopping assistant's recommendation: it may instead influence which prefer

agentsarxiv-cs-lg

Self-Aligned Forcing: Streaming Video Diffusion with Differentiable Noisy History

arXiv:2609.38114v1 Announce Type: new Abstract: Autoregressive video diffusion enables interactive streaming generation, but suffers from error accumulation over long rollouts. Self-rollout training r

safetyarxiv-cs-cv

Simultaneous Neural Optimal Transport

arXiv:2609.37424v1 Announce Type: cross Abstract: Optimal Transport (OT) provides a principled framework for learning transformations between probability distributions from unpaired samples. In many a

safetyarxiv-cs-ai

SkillCome: Group Contrast Skill Optimization with Dual Memory

arXiv:2609.37128v1 Announce Type: new Abstract: Skill evolution improves the capabilities of large language models by analyzing trajectories generated under a given skill and modifying the skill accor

agentsarxiv-cs-ai

Spatial-OPSD: Self-Improving Spatial Reasoning via Label-Free Self-Distillation

model-releasesarxiv-cs-cv

arXiv:2609.37055v1 Announce Type: new Abstract: Vision-language models (VLMs) increasingly operate in embodied and spatially grounded settings, where accurate understanding of depth, viewpoint, and th

SPLASH: Switching Parallel Layouts of Attention with Seamless Handoff for LLM Serving

arXiv:2609.37626v1 Announce Type: cross Abstract: No single way of parallelizing attention serves large language models well under all loads. Low concurrency favors tensor parallelism, many independen

StateTape: Action-Conditioned Evidence Lifecycle Modeling for Long-Horizon Coding Agents

arXiv:2609.36319v1 Announce Type: new Abstract: Despite the recent success of coding agents built on large language models, it remains challenging to run them over long horizons, since every observati

Support-Set Target Leakage in Relational Foundation Models during In-Context Learning: Impact, Detection, and Mitigation

arXiv:2609.36384v1 Announce Type: new Abstract: Relational in-context learning (ICL) conditions predictions on the labeled support examples and their linked tables, creating a failure mode when the su

T^2Mem: Learning Test-Time Memory for Robotics

model-releasesarxiv-cs-ro

arXiv:2609.36720v1 Announce Type: new Abstract: Memory-dependent robotic manipulation requires policies to use information that is no longer available in the current observation. Retaining history alo

Tail-Influence Sampling for CVaR Policy Evaluation

arXiv:2609.38096v1 Announce Type: new Abstract: Policies with similar mean returns can differ sharply in rare failures, yet estimating lower-tail conditional value-at-risk (CVaR) accurately can requir

safetyarxiv-cs-lg

TaRL: Learning General and Physical Rewards from Tactile Demonstrations

arXiv:2609.36785v1 Announce Type: new Abstract: Contact-rich manipulation requires robots to sequence precise contacts, maintain stable grasps, and apply directed forces. Reinforcement learning (RL) c

local-aiarxiv-cs-ro

Applications

TaskBridge: Bridging Unsupervised Tabular Anomaly Detection and In-Context Learning via Virtual Tasks

arXiv:2609.36968v1 Announce Type: new Abstract: Unsupervised tabular anomaly detection (TAD) aims to identify anomalous rows in tabular data using normal training samples. While conventional methods r

applicationsarxiv-cs-lg