Search: “inference”

FEAST: Federated Shared-Space Training for Resource-Heterogeneous Clients

model-releasesarxiv-cs-lg

arXiv:2608.09250v1 Announce Type: new Abstract: Federated learning (FL) must serve devices with varying computational capabilities. A fixed model cannot suit all devices, while training one model per

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Agents

Keep It Simple: Multi-Key Episodic Memory Retrieval for Ultra-Long Video Understanding

DGX agent

arXiv:2608.07663v1 Announce Type: cross Abstract: When videos extend from hours to days, directly processing them end-to-end becomes impractical for current Multi-modal Large Language Models (MLLMs).

agentsarxiv-cs-ai

11 Aug 2026

LLMVisor: A Real-Time Latency Attribution Model for Multi-Tenant LLM Serving

arXiv:2608.08382v1 Announce Type: new Abstract: As LLM inference shifts to multi-tenant GPU clusters, co-batching improves throughput but obscures per-tenant usage and limits control. Enabling fractio

Predicting blood clot growth from sparse post-onset measurements with latent neural differential equations

model-releasesarxiv-cs-lg

arXiv:2608.08165v1 Announce Type: new Abstract: Computational models of blood clotting improve understanding of thrombus formation, but their clinical application remains limited because many model in

Applications

Reading Cognition as Decisions Unfold in Words: A Factorized Inverse Decision Model

arXiv:2608.09222v1 Announce Type: new Abstract: Inverse decision modeling infers latent properties of decision processes from observed behavior, but existing formulations rely primarily on action traj

applicationsarxiv-cs-cl

Reflex First, Reflect Later: Latency-Aware Embodied LLM Agents for Dynamic Response

arXiv:2506.07223v2 Announce Type: replace Abstract: Large language models (LLMs) have substantially improved the planning capabilities of embodied agents, enabling their deployment in dynamic and safe

safetyarxiv-cs-ai

Applications

Rethink Before You Execute: Adaptive Execution for World Action Models

arXiv:2608.09492v1 Announce Type: new Abstract: World Action Models (WAMs) jointly predict future actions and the evolution of the environment. At each inference, a WAM generates a chunk of actions an

applicationsarxiv-cs-ro

Test-Time Augmentation for LLMs: When Input Diversity Beats Output Diversity at Matched Compute

arXiv:2608.09351v1 Announce Type: cross Abstract: Test-time scaling improves LLM accuracy but multiplies inference cost, making the accuracy gained per unit of compute the metric that matters in deplo

GRASP: Reinforcing Language Model Anonymizers with Group Relative Policy Optimization

arXiv:2608.06526v1 Announce Type: new Abstract: Large language models can infer sensitive personal attributes, such as age, location, and occupation, from ordinary text, turning everyday writing into

10 Aug 2026

Tutorials

Learning to Predict Middle-Layer Attention in MLLMs for Visual Token Prunin

arXiv:2608.06411v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) achieve strong performance across diverse vision-language tasks, but their efficiency is limited by the cost of

tutorialsarxiv-cs-ai

10 Aug 2026

Afford-X: Generalizable and Slim Affordance Reasoning for Task-oriented Manipulation

model-releasesarxiv-cs-cv

arXiv:2503.03556v3 Announce Type: replace Abstract: Object affordance reasoning, the ability to infer object functionalities based on physical properties, is fundamental for task-oriented planning and

7 Aug 2026

SkillZip: Contract-Preserving Graph Compression for Scalable Agent Skill Libraries

arXiv:2608.05604v1 Announce Type: cross Abstract: Large Language Models (LLMs) increasingly act as agents whose procedural knowledge is stored in reusable skill packages and loaded at inference time.

agentsarxiv-cs-ai

7 Aug 2026

ViSR-KGC: Visual Subgraph Reasoning with Vision-Language Models for Multimodal Knowledge Graph Completion

arXiv:2608.05833v1 Announce Type: new Abstract: Knowledge graph completion (KGC) aims to infer missing entities or relations from incomplete graph structures, and has evolved into multimodal knowledge

7 Aug 2026

Flash-VAED: Plug-and-Play VAE Decoders for Efficient Video Generation

arXiv:2602.19161v2 Announce Type: replace Abstract: Latent diffusion models have enabled high-quality video synthesis, yet their inference remains costly and time-consuming. As diffusion transformers

safetyarxiv-cs-cv

6 Aug 2026

Masked diffusion enables coherent beat tracking

arXiv:2608.04624v1 Announce Type: cross Abstract: Current neural networks for beat tracking generate invalid outputs, such as consecutive downbeats and erratic tempo changes, even when these are not p

6 Aug 2026

Relevant but Incomplete: Referential Dangling as a Paradigm-Level Failure Mode in Hard Prompt Compression

arXiv:2608.04569v1 Announce Type: new Abstract: Hard prompt compression reduces long-context inference cost by independently scoring tokens, sentences, or chunks and retaining the highest-scoring unit

6 Aug 2026

A Graph Signal Processing Perspective on Numerical Sequence Representations in LLM In-Context Learning

arXiv:2608.03015v1 Announce Type: cross Abstract: Pretrained large language models (LLMs) have demonstrated in-context learning (ICL) capabilities for numerical inference over sequences serialized as

Aligning Large Vision-Language Models at Test Time: A Trajectory-Guided Structured Sampling Approach

arXiv:2608.03204v1 Announce Type: cross Abstract: Post-training reinforcement learning (RL) algorithms are commonly used to align large vision-language models (LVLMs) with human intent and the require

Mixed-Initiative Human-Robot Teaming under Suboptimality with Online Bayesian Adaptation

arXiv:2403.16178v2 Announce Type: replace-cross Abstract: For effective human-agent teaming, robots and other artificial intelligence (AI) agents must infer their human partner's abilities and behavio

agentsarxiv-cs-ai

Output-Aware Rotation for INT2 KV-Cache Quantization

arXiv:2608.02691v1 Announce Type: cross Abstract: The key-value (KV) cache has become a major memory and bandwidth bottleneck in long-context large language model inference, making ultra-low-bit quant

PRISMA: Improving the Accuracy-Latency Frontier of Diffusion-based PDE Solvers Using Physics-Informed Spectral Attention

arXiv:2512.01370v2 Announce Type: replace-cross Abstract: Diffusion-based solvers for partial differential equations (PDEs) are often bottle-necked by slow gradient-based test-time optimization routin

The Transformer Revolution, Part 1: Dynamic Processing through Output- Weight Interconnections

arXiv:2608.03921v1 Announce Type: new Abstract: This paper offers a new interpretation of the Transformer during inference. Against the 'stochastic parrot' view that large language models merely repro

Applications

CARE: A Cascaded Framework for Efficient and Reliable Time Series Anomaly Detection

arXiv:2608.01885v1 Announce Type: new Abstract: While deep learning models have achieved state-of-the-art performance in time series anomaly detection, their complex architectures incur substantial in

applicationsarxiv-cs-lg

Practical Online KV Cache Compaction for LLM Agents: An Empirical Study

arXiv:2608.00902v1 Announce Type: new Abstract: LLM agents accumulate long trajectories of reasoning steps, tool calls, and environment feedback, making the KV cache a major inference bottleneck. KV c

agentsarxiv-cs-cl

RamanPFN: learning from Raman spectral structure with a tabular foundation model

model-releasesarxiv-cs-lg

arXiv:2608.02157v1 Announce Type: new Abstract: Raman spectroscopy enables non-destructive, label-free molecular characterization across materials science, biomedicine and process monitoring. Predicti

RSC-GestureNet: Reliability-Aware Selective Causal Recognition of Chinese Traffic Police Gestures

model-releasesarxiv-cs-cv

arXiv:2608.02200v1 Announce Type: new Abstract: Traffic police gestures are safety-critical perception cues for autonomous driving. A deployable recognizer must infer commands causally from continuous

ScrambleToolBench: Agents Search Exhaustively Even When Their Own Map Points to the Next Step

arXiv:2608.02358v1 Announce Type: new Abstract: To operate robustly in open-world environments, autonomous agents should be able to infer the behavior of unfamiliar systems through interaction alone,

UniSim-SLAM: Feed-Forward SLAM with Unified Sim(3) Optimization

arXiv:2608.01706v1 Announce Type: new Abstract: Recent geometric foundation models enable feed-forward inference for SLAM, but their predictions are strongly dependent on the input view set, which lea

researcharxiv-cs-cv

ResKV: Reconstructing Omitted Attention Contributions for Fixed-Budget KV Cache Compression

arXiv:2607.29591v1 Announce Type: new Abstract: KV cache compression is essential for efficient long-context inference. Existing eviction methods permanently discard unselected tokens and consequently

researcharxiv-cs-cl

3 Aug 2026

Safe Vision Language Action Models via Barrier Enhanced Flow Matching

model-releasesarxiv-cs-ro

arXiv:2607.29569v1 Announce Type: new Abstract: This article presents a modular inference framework that integrates Flow Matching generative models with formal Control Barrier Function (CBF) safety gu

3 Aug 2026

Hardware

AgenticCANN: Automated Ascend C Operator Generation via Knowledge-Augmented Agentic Evolution

arXiv:2607.26661v1 Announce Type: new Abstract: Ascend C operator optimization is critical for NPU (Neural Processing Unit) inference performance but requires deep hardware expertise.While large langu

hardwarearxiv-cs-ai

Calibrate Before Reason: Robust Visual Token Reduction against Semantic Drift in VLMs

arXiv:2607.27700v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) suffer from prohibitive inference overhead due to long sequences of visual tokens. However, existing visual token re

researcharxiv-cs-cv

Corrigible Assistance in One Round: Pragmatic-Pedagogic Best Response

arXiv:2607.27508v1 Announce Type: new Abstract: Assistance games formalize human-robot collaboration under asymmetric information: the human knows the goal, while the robot must infer it from observat

safetyarxiv-cs-ro

Tutorials

PhiZero: A World Model Built Around Physical Language

arXiv:2607.28624v1 Announce Type: new Abstract: We introduce PhiZero, a physical world model built around physical language, a compact discrete representation of world-state transitions. Existing phys

tutorialsarxiv-cs-cv

Hardware

ROCS: Request-Oriented Compute Sharing for Efficient Large-Scale Recommendation

arXiv:2607.27744v1 Announce Type: new Abstract: Modern recommendation models gain prediction quality by scaling feature-interaction and sequence modules, but production cost constraints cap how far sy

hardwarearxiv-cs-lg

SVR: Self-Verifying Refinement via Joint Verdict-Confidence Reinforcement Learning for Adaptive Test-Time Compute

arXiv:2607.28457v1 Announce Type: cross Abstract: Scaling test-time computation can improve language-model reasoning, but uniform budgets waste computation on easy inputs, while verifier-guided refine

safetyarxiv-cs-cl

Tycho: Active Abstraction with Programmatic World Models for ARC-AGI-3

model-releasesarxiv-cs-cv

arXiv:2607.28287v1 Announce Type: cross Abstract: ARC-AGI-3 turns abstraction into an interactive problem of skill acquisition. A player must infer an unfamiliar game's rules, hidden state, and goal w

Write-Safe Flow Field Mapping under Ambiguous Onboard Sensing and Localization Drift

arXiv:2607.27713v1 Announce Type: new Abstract: Mobile robots can infer local flow structure from onboard sensing, but a locally plausible estimate is not always safe to write into a global map. Simil

local-aiarxiv-cs-ro

ARC-Encoder: learning compressed text representations for large language models

arXiv:2510.20535v2 Announce Type: replace Abstract: Recent techniques such as retrieval-augmented generation or chain-of-thought reasoning have led to longer contexts and increased inference costs. Co

30 Jul 2026

Hardware

BATS: Resource-Efficient Volumetric Segmentation with Boundary-Aware Mixed-Resolution Tokens

arXiv:2607.26829v1 Announce Type: new Abstract: Many high-performing volumetric segmentation models maintain dense multi-scale feature maps, leading to high activation memory and inference cost. We pr

hardwarearxiv-cs-cv

30 Jul 2026

Minimizing Targeted Activations: Input-Only Suppression of Evaluation-Awareness Latents in Large Language Models

arXiv:2607.25907v1 Announce Type: cross Abstract: Activation steering controls model behavior by editing internal activations at inference time. We study its input-side dual: optimizing a fluent promp

Neuromorphic Diffusion Language Models: Addressing Compute and Memory Bottlenecks via Sparsity and Block Denoising

arXiv:2607.24841v1 Announce Type: new Abstract: Autoregressive (AR) large language models (LLMs) are inherently inefficient at inference time because each generated token requires accessing the full s

Stemma: Induced Decision Regions Reveal LLM Provenance

arXiv:2607.25880v1 Announce Type: cross Abstract: LLM provenance testing asks whether a suspect LLM belongs to the same lineage as a source. Existing black-box methods largely infer this relationship

Towards real-time surrogate-free Bayesian inversion for neutron reflectometry

arXiv:2509.06924v3 Announce Type: replace Abstract: Neutron reflectometry (NR) is a key enabling technology for many areas of scientific development. Although the forward reflectivity model is well-kn

researcharxiv-cs-lg

Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents

arXiv:2607.15263v3 Announce Type: replace-cross Abstract: Security-agent evaluations commonly measure peak offensive capability under generous inference budgets, emphasizing vulnerability discovery, e

agentsarxiv-cs-ai

CADER: Confidence-Aware Dynamic Evidence Reasoning for Long-Video Understanding

arXiv:2607.24582v1 Announce Type: cross Abstract: Long-video understanding increasingly relies on large vision-language models and tool-augmented reasoning, but most systems apply the same inference p

Intuitionistic j-Do-Calculus in Topos Causal Models

arXiv:2510.17944v2 Announce Type: replace-cross Abstract: In this paper, we generalize Pearl's do-calculus to an Intuitionistic setting called j-stable causal inference inside a topos of sheaves. Our

LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models

arXiv:2411.00918v5 Announce Type: replace-cross Abstract: Mixture of experts (MoE) architectures have become a cornerstone for scaling up and are a key component in most large language models such as