Search: “inference”

Disagreement-Guided Weak-to-Strong Routing

arXiv:2610.22245v1 Announce Type: new Abstract: Small language models are increasingly deployed on edge devices and robotic systems to meet cost and latency constraints, yet their limited capabilities

local-aiarxiv-cs-ai

DropKV: Decoupling Residual-Output Perturbation for Near-Optimal KV-Cache Eviction

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DGX agent

arXiv:2610.22130v1 Announce Type: new Abstract: Key-value (KV) cache management has become a critical bottleneck for scaling Large Language Models (LLMs) to long-context scenarios due to linear memory

researcharxiv-cs-ai

16 Oct 2026

FlowBudget: Training-Free Sampling-Budget Estimation for Flow Matching Models

arXiv:2610.20636v1 Announce Type: cross Abstract: Sampling from continuous flow-based generators such as flow matching models requires numerical ODE or SDE integration, making inference cost depend on

researcharxiv-cs-cv

From Long Context to Selective Memory:A Survey of Memory-Centric Compression for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2610.21165v1 Announce Type: new Abstract: Long-context capability has become essential for large language models (LLMs) to handle complex tasks, yet continuously expanding the context window doe

Tutorials

How Much Physics Can Vision Learn from Audio? Probing and Distilling Damping Structure

arXiv:2610.22221v1 Announce Type: new Abstract: Physical understanding is crucial for decision making, yet vision models struggle to infer properties such as damping that govern how materials behave.

tutorialsarxiv-cs-cv

Tutorials

Latent Annealed Posterior Sampling with a Variance-Preserving Bridge for Sparsely Observed Random Fields

arXiv:2610.20659v1 Announce Type: cross Abstract: Posterior inference for random fields from sparse observations presents two major challenges: accurately characterizing complex spatial uncertainty an

tutorialsarxiv-cs-lg

Mallea: Building, Steering, and Memorizing Worlds with Coding Agent

arXiv:2610.21283v1 Announce Type: new Abstract: Code world models represent world dynamics through explicit state and executable rules. We investigate how to coordinate object representations, behavio

agentsarxiv-cs-ai

Policy-Aligned Predictive Verification for Adaptive VLA Action-Chunk Execution

arXiv:2610.21434v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies generate action sequences that reduce repeated inference, but deciding how much of each sequence to execute is c

safetyarxiv-cs-lg

Sparse Attention for Video Generation Acceleration via Growing Sparsity and Reduced Search

arXiv:2610.21129v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) dominate video generation but suffer from high inference cost due to the quadratic complexity of self-attention. Sparse at

researcharxiv-cs-cv

Applications

T2-z: Test-Time Optimization of Environment Latents for Robotic World Models

arXiv:2610.22364v1 Announce Type: cross Abstract: Predicting how the world responds to an action requires more than what can be seen: robots must account for environmental factors that are neither dir

applicationsarxiv-cs-ai

Where to Steer: Input-Dependent Layer Selection for Steering Improves LLM Alignment

arXiv:2604.03867v2 Announce Type: replace Abstract: Steering vectors have emerged as a lightweight and effective approach for aligning large language models (LLMs) at inference time, enabling modulati

safetyarxiv-cs-lg

A Reference Architecture for Integrating Agentic AI into Enterprise Software: Responsibilities, Interactions, and Variability

arXiv:2610.14818v1 Announce Type: new Abstract: Agentic AI moves generative AI applications toward systems that coordinate reasoning, enterprise context, model inference, and external actions. Integra

agentsarxiv-cs-ai

Action Jets: Learning the Local Shape of the Action-conditioned Data Manifold

arXiv:2610.19007v1 Announce Type: new Abstract: World models are a powerful means of reasoning and planning, but many of these action-conditioned predictive models are high dimensional and computation

Alignment Faking - the Train -> Deploy Asymmetry: Through a Game-Theoretic Lens with Bayesian-Stackelberg Equilibria

arXiv:2511.17937v2 Announce Type: replace Abstract: Alignment faking is a form of strategic deception in AI in which models selectively comply with training objectives when they infer that they are in

Beyond Successful Play: Diagnosing Opponent Modeling in Large Language Models

arXiv:2610.17310v1 Announce Type: new Abstract: Language-model agents are expected to adapt to others whose behavior changes through interaction. Yet adaptation may rely on learned behavioral patterns

DD-GBP: Anytime Multi-Arm Planning and Continuous Execution via Distributed Dynamic Gaussian Belief Propagation

arXiv:2610.20460v1 Announce Type: new Abstract: Safely executing long-horizon multi-arm tasks online in complex dynamic environments remains challenging. We propose a new distributed dynamic Gaussian

local-aiarxiv-cs-ro

Delta Tokenizer: Reference-Identical Tokenization of Session Deltas and Segment-Parallelism for Long Prompts on Multicore CPUs

arXiv:2610.19801v1 Announce Type: new Abstract: An agent that drives an LLM sends the model the same conversation again and again, and each turn adds only a little text at the end. Inference engines r

agentsarxiv-cs-cl

ECMR: Evidence-Aware Deliberation Control for Multi-Agent LLM Reasoning

arXiv:2610.17869v1 Announce Type: new Abstract: Multi-agent Large Language Model (LLM) systems typically commit to a deliberation protocol before inference. A fixed protocol cannot allocate computatio

agentsarxiv-cs-ai

Fascinating paper from Google DeepMind. They studied a market where AI agents bid to answer each user prompt. Each agent bids its expected r…

Fascinating paper from Google DeepMind. They studied a market where AI agents bid to answer each user prompt. Each agent bids its expected reward minus its inference cost. A first-price auction is sim

agentsdair-ai--x

GesBench: When and Where Do Multimodal Language Models Perceive Social Meaning?

arXiv:2610.15129v1 Announce Type: new Abstract: Human social perception is incremental: we infer intent before an utterance is complete, revise our interpretation as new cues arrive, and attend to spe

Applications

Have You Been Convinced? A Neuro-symbolic Argumentation Reasoning Approach to Detecting Persuasiveness in ChangeMyView Discussions

arXiv:2610.15091v1 Announce Type: cross Abstract: Argument structures represent how individual arguments interact within a discourse. However, leveraging these structures to infer meaningful knowledge

applicationsarxiv-cs-ai

Instructions Are Evidence, Not Objectives: Measuring Outcome Alignment of Agents

arXiv:2610.17757v1 Announce Type: new Abstract: Large language model agents can follow complex human instructions to solve real-world tasks. In practice, however, initial instructions are often incomp

KiToke: Distribution-Aware Token Compression for Video Large Language Models

arXiv:2604.03414v2 Announce Type: replace Abstract: Video Large Language Models (Video LLMs) achieve strong performance on video understanding tasks but suffer from high inference costs due to the lar

Language Steering for Multilingual In-Context Learning

model-releasesarxiv-cs-cl

arXiv:2602.02326v3 Announce Type: replace Abstract: If multilingual language model representations contain separable language-associated structure, then shifting between languages may require only sim

MAPLE: A Multi-Axis Parametric Knowledge Extraction Lens for LLM Evaluation

arXiv:2610.19827v1 Announce Type: cross Abstract: LLMs absorb vast knowledge from training data, yet their inherently probabilistic nature offers no guarantee that this knowledge will surface in their

researcharxiv-cs-cl

Mitigating Cross-Modal Hallucinations by Correcting Modality Misrouting in Omnimodal LLMs

arXiv:2610.18141v1 Announce Type: new Abstract: Omnimodal large language models (OLLMs) are susceptible to cross-modal hallucinations under audio-visual interference. We find that, for a substantial f

researcharxiv-cs-ai

MobiGuide: Vocabulary-Guided Online Recovery for Mobile Manipulation

arXiv:2604.01567v2 Announce Type: replace Abstract: A central challenge in mobile manipulation is preserving multiple plausible action modes while remaining reactive during execution. For example, gra

local-aiarxiv-cs-ro

Qwen3.8FN vLLM vs. llama.cpp vs Ninfer6000

model-releasesr-localllama

I saw u/lkarlslund 's post just over a week ago regarding Ninfer6000 (a fork of Ninfer specifically tuned for 6000 blackwell and Qwen3.8-Flash-Next) and figured 'Hey I'm an idiot & bought one of those

Recursive Improvement of a Differentiable Scientific Software Ecosystem

arXiv:2610.04561v2 Announce Type: replace Abstract: Differentiable programming connects scientific computation with gradient-based inference, learning and design. Extending these capabilities across a

REVEAL: Reverse Engineering Agentic Latents from Frontier-Model Traces

arXiv:2610.16288v2 Announce Type: new Abstract: Frontier LLM agents perform complex interactive tasks, but their inference costs motivate transferring their experience to smaller open-source agents. D

RoTA-Bench: Evaluating 3D Spatial Reasoning through Interactive Projection Alignment

arXiv:2610.17665v2 Announce Type: new Abstract: Can vision-language models turn 2D observations into 3D understanding that supports precise action? This requires inferring object geometry, anticipatin

StreamErase: Towards Ultra-Fast Streaming Video Erasing

arXiv:2610.20137v1 Announce Type: new Abstract: Current video object removal methods suffer from prohibitive latency (minutes per video) and non-causal processing that prevents real-time interaction.

Tutorials

The Impact of Detector Architecture, Model Scale, and Scene Density on Multi-Pedestrian Tracking

arXiv:2610.19369v1 Announce Type: new Abstract: Pedestrian tracking in video is important for applications such as surveillance and scene analysis, but it becomes more challenging in crowded scenarios

tutorialsarxiv-cs-cv

The Sharp Directions Are Against You: Curvature Analysis of Activation Steering

arXiv:2610.16084v1 Announce Type: new Abstract: Activation steering adds a vector to a language model's internal representations at inference time. It is a lightweight alternative to fine-tuning for b

WeFair: Fidelity-Aware Alignment from Human Feedback for Personalized Query Rewriting in Short-Video Search

arXiv:2610.16927v1 Announce Type: new Abstract: Short-video search requires compact query rewriters that infer personalized intent from brief, ambiguous queries under strict latency constraints. The c

safetyarxiv-cs-ai

176 t/s decode and 6,450 t/s prefill with Q4 Qwen-3.8 Flash-Next on 2xR9700 + 64GB DDR5 using Deadcode's Radiance engine

model-releasesr-localllama

https://preview.redd.it/kudj7xii5ivh1.png?width=1508&format=png&auto=webp&s=07712e81310b81aceb2cf8f4d8a7c2eadeb0c304 Just built a new PC, full parts list is here. I am using Deadcode's Radiance infere

A Behavior-first approach to Multi-Intention Inverse Reinforcement Learning

arXiv:2602.07496v2 Announce Type: replace Abstract: Inverse Reinforcement Learning (IRL) seeks to infer reward functions from expert demonstrations. When demonstrations originate from multiple experts

AI-Assisted Tumor-Growth Law Discovery from Sparse Data: Refitting and LLM-Based Ranking

arXiv:2610.16891v1 Announce Type: new Abstract: Inferring tumor-growth laws from sparse, noisy observations requires more than accurate curve fitting. We study an AI-assisted workflow involving symbol

Barrier-Constrained Guidance For Real-time Asynchronous VLA Execution

arXiv:2610.14997v1 Announce Type: new Abstract: While asynchronous execution enables VLA models to operate in real-time environments by predicting the next chunk during execution, it inevitably introd

safetyarxiv-cs-ro

Hardware

BELT : BEhavior-Aligned Low-Rank KV Cache Compression with Learned Top-k Rank Allocation

arXiv:2610.17966v1 Announce Type: new Abstract: Long-context inference makes the key-value (KV) cache a major memory bottleneck for large language models. We propose BELT, a low-rank KV cache compress

hardwarearxiv-cs-lg

Carve VFM: Carving Specialists out of Generalists, Automatic Task-Specific Compression of Vision Foundation Models

arXiv:2610.16813v1 Announce Type: new Abstract: Vision foundation models (VFMs) provide transferable visual representations, but their inference cost limits deployment in many settings. Fine-tuning sp

Hardware

Competition Domains Matter: Selective Head Globalization for Training-Free Sparse Attention in Video Diffusion Transformers

arXiv:2610.14672v1 Announce Type: new Abstract: Training-free sparse attention is a practical route to efficient video diffusion transformer inference, yet existing methods typically fix the competiti

hardwarearxiv-cs-cv

Context-Aware Precision Scheduling for Small Language Models

model-releasesarxiv-cs-lg

arXiv:2610.15640v1 Announce Type: new Abstract: Small language models (SLMs) used as on-device agents must balance accuracy and latency as their context grows. Mixed precision helps manage this tradeo

Contrastive Covariance Subspaces for Activation Steering

arXiv:2610.14025v1 Announce Type: new Abstract: Activation steering controls large language model behavior by adding a direction to hidden activations during inference. For steering to work well, that

Delta Flow Matching for Robot Foundation Models

arXiv:2610.15794v1 Announce Type: new Abstract: Flow matching is a common generative recipe for robot foundation models. Vision-language-action models (VLAs) generate action chunks, while world-action

safetyarxiv-cs-ro

Explaining Heterogeneous Treatment Effects with Causal Forests and the Hoeffding Functional Decomposition

arXiv:2610.16447v1 Announce Type: cross Abstract: The estimation of heterogeneous treatment effects is a central objective of causal inference. However, state-of-the-art algorithms to solve this task

exttt{NFDiag}: High-dimensional MCMC Convergence Diagnosis with Normalizing Flows

arXiv:2610.16574v1 Announce Type: cross Abstract: Accurately assessing the convergence of Monte Carlo Markov Chains is crucial for ensuring their validity in Bayesian inference problems. However, conv

FlashVSR+: Efficient Video Super-Resolution via Hybrid Attention and Reward-Yield Distribution Matching

arXiv:2610.17552v1 Announce Type: new Abstract: Recent video super-resolution (VSR) models achieve efficient one-step generation through diffusion distillation. However, high-resolution inference rema

local-aiarxiv-cs-cv