Search: “inference”

Cross-LLM Consistency in Inference: Evidence from Shared Interactions

arXiv:2606.08129v1 Announce Type: new Abstract: Large language models (LLMs) differ in architecture, training data, and optimization procedures, yet they may still develop similar internal inference p

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Disentangling Latent Risk Pathways via Bayesian Hypergraph Inference

DGX agent

arXiv:2606.07677v1 Announce Type: cross Abstract: Electronic health records (EHR) pose large-scale multi-disease modeling problems in which many outcomes are rare and strongly influenced by shared ris

researcharxiv-cs-lg

9 Jun 2026

FuseFSS: Efficient Secure LLM Inference with Function Secret Sharing

arXiv:2606.09551v1 Announce Type: cross Abstract: Two-server secure inference allows a client to query a hosted large language model (LLM) without revealing prompts or embeddings. Recent GPU systems b

hardwarearxiv-cs-ai

In-Context Learning of Temporal Point Processes with Foundation Inference Models

arXiv:2509.24762v3 Announce Type: replace Abstract: Modeling event sequences of multiple event types with marked temporal point processes (MTPPs) provides a principled way to uncover governing dynamic

LLM Inference at the Edge: Mobile, NPU, and GPU Performance Efficiency Trade-offs Under Sustained Load

arXiv:2603.23640v2 Announce Type: replace-cross Abstract: Deploying large language models on-device for always-on personal agents demands sustained inference from hardware tightly constrained in power

REMEDI: A Benchmark for Retention and Unlearning Evaluation in Multi-label Clinical Disease Inference

arXiv:2606.07141v1 Announce Type: cross Abstract: Language models trained for clinical disease inference are trained on patient data, which may include sensitive and private information, and data owne

8 Jun 2026

Flow Matching Calibration for Simulation-Based Inference under Model Misspecification

arXiv:2509.23385v5 Announce Type: replace-cross Abstract: Simulation-based inference (SBI) is transforming experimental sciences by enabling parameter estimation in complex non-linear models from simu

4 Jun 2026

Inference-Time Vulnerability Beyond Shallow Safety: Alignment Along Generation Trajectories

arXiv:2606.04778v1 Announce Type: new Abstract: Safety-aligned Large Language Models (LLMs) remain vulnerable to interventions during inference that redirect generation toward harmful outputs. Recent

safetyarxiv-cs-ai

4 Jun 2026

SharedRequest: Privacy-Preserving Model-Agnostic Inference for Large Language Models

arXiv:2606.05004v1 Announce Type: cross Abstract: With the widespread deployment of public large language models (LLMs) such as ChatGPT, protecting user prompt privacy has become an increasingly criti

4 Jun 2026

NetKV: Network-Aware Decode Instance Selection for Disaggregated LLM Inference

arXiv:2606.03910v1 Announce Type: cross Abstract: Disaggregated LLM inference forces the KV cache to traverse the datacenter network before decoding begins, so transfer time enters directly into the T

local-aiarxiv-cs-ai

3 Jun 2026

Qift: Shift-Friendly No-Zero W2 Post-Training Quantization for Rotated W2A4/KV4 LLM Inference

arXiv:2606.02823v1 Announce Type: new Abstract: Two-bit weight quantization is attractive for memory-efficient LLM inference, but the standard W2 level set {-2,-1,0,+1} often collapses under aggressiv

3 Jun 2026

Resource-Constrained Adaptive Inference for Sequential Pricing

arXiv:2606.03736v1 Announce Type: cross Abstract: Resource-constrained pricing controllers can make fixed-price inference impossible: the controller's resource state may remove the target price neighb

local-aiarxiv-cs-lg

3 Jun 2026

Bandit Simulation for Average Reward Inference

arXiv:2606.00913v1 Announce Type: cross Abstract: Multi-arm bandit algorithms are increasingly used in online platforms, clinical trials, and social science experiments, but valid statistical inferenc

Beyond Task-Agnostic: Task-Aware Grouping for Communication-Efficient Multi-Task MoE Inference

arXiv:2606.01007v1 Announce Type: cross Abstract: Sparsely activated Mixture-of-Experts (MoE) models scale capacity via conditional computation, but distributed inference suffers from cross-GPU expert

local-aiarxiv-cs-ai

Bit-Exact AI Inference Verification Without Performance Tradeoffs

arXiv:2606.00279v1 Announce Type: cross Abstract: Verifying claims about AI workloads is a pre- requisite for credible AI governance of covert adversaries (who comply with monitoring only when detecti

hardwarearxiv-cs-lg

Differentially Private Datastore Generation for Retrieval-Augmented Inference

arXiv:2606.01413v1 Announce Type: cross Abstract: It is crucial for modern on-device AI systems that rely on retrieval-augmented inference to release and share datastores without compromising individu

Permissive Safety Through Trusted Inference: Verifiable Belief-Space Neural Safety Filters for Assured Interactive Robotics

arXiv:2606.02562v1 Announce Type: cross Abstract: Autonomous robots that interact with people must make safe and efficient decisions under human-induced uncertainty, such as their preferences, goals,

Threading Optimization for Vision-Language-Action Model Inference in Low-Cost Smart Agricultural Manipulation

arXiv:2606.00966v1 Announce Type: new Abstract: Vision-Language Action (VLA) models continue to face challenges such as slow inference speed and difficulty performing fine-grained motion adjustments,

safetyarxiv-cs-ro

Causal Evaluation of Membership Inference Attacks

arXiv:2602.02819v3 Announce Type: replace Abstract: Membership Inference Attacks (MIAs) aim to distinguish training points (members) from unseen data (non-members), and are widely used to quantify mem

1 Jun 2026

Distributionally Robust Set Representation Learning Under Inference-Time Element Corruption

arXiv:2605.30089v1 Announce Type: new Abstract: Standard Set Representation Learning methods typically excel on curated data but often overlook the challenge of inference-time element corruption. This

29 May 2026

Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series

arXiv:2605.30292v1 Announce Type: cross Abstract: Conformal prediction methods enjoy strong theoretical and empirical predictive inference performance, provided the data is exchangeable, and predictor

29 May 2026

ASTRA: Communication-Efficient Acceleration for Multi-Device Transformer Inference

arXiv:2505.19342v2 Announce Type: replace-cross Abstract: Multi-device inference can reduce Transformer latency by parallelizing computation. However, existing methods require high inter-device bandwi

Deep Neural Network Training as Random Effects: An Optimization-Inference Duality

arXiv:2605.27991v1 Announce Type: cross Abstract: Deep neural networks (DNNs) have achieved remarkable empirical success, yet their training dynamics remain understood mainly from optimization rather

GenSBI: Generative Methods for Simulation-Based Inference in JAX

arXiv:2605.27499v1 Announce Type: new Abstract: Flow and diffusion generative models have established themselves as widely adopted density estimators for simulation-based inference (SBI), extending na

LLM Zeroth-Order Fine-Tuning is an Inference Workload

arXiv:2605.28760v1 Announce Type: new Abstract: Zeroth-order (ZO) fine-tuning is attractive for large language models because it replaces backpropagation with forward objective evaluations. Existing i

Agents

MRMMIA: Membership Inference Attacks on Memory in Chat Agents

arXiv:2605.27825v1 Announce Type: cross Abstract: Membership inference attacks (MIAs) test whether a target data record belongs to a system's private data, and have become a standard tool to measure p

agentsarxiv-cs-lg

Semiparametrically Efficient Inference for Kernel Measures of Noise Heterogeneity

arXiv:2605.27526v1 Announce Type: cross Abstract: We develop semiparametrically efficient inference for kernel measures of noise heterogeneity in additive noise models. In many applications, the regre

Stop Suppressing the Tail: Causal Inference for Extreme Events

arXiv:2605.27474v1 Announce Type: cross Abstract: Estimating how an outcome responds to a continuous treatment (the Average Dose-Response Function, or ADRF) is a core causal-inference primitive. Howev

UNIQUE: Universal Top-k Sparse Attention for Training-free Inference and Sparsity-aware Training

arXiv:2605.27740v1 Announce Type: new Abstract: Long-context inference in large language models (LLMs) is bottlenecked by the linear growth of the self-attention key-value (KV) cache. Top-k sparse att

researcharxiv-cs-cl

Whose Is This?: Context-Aware Object Ownership Inference with Uncertainty-Guided Questioning

arXiv:2605.28087v1 Announce Type: new Abstract: Service robots must infer object ownership to correctly interpret instructions such as 'bring me my cup.' However, ownership is a latent attribute that

researcharxiv-cs-ro

Agents

Stateful Inference for Low-Latency Multi-Agent Tool Calling

arXiv:2605.26289v1 Announce Type: new Abstract: Multi-agent tool calling is becoming the dominant interaction pattern for LLM-based systems, yet existing inference frameworks treat each tool call as a

agentsarxiv-cs-lg

27 May 2026

Beyond Inference-Only Deployment: Comparing Weight-Based Consolidation Against Cascading Compaction

arXiv:2605.24657v1 Announce Type: new Abstract: Major LLM platforms deploy models in an inference-only configuration: the model serves requests but never updates per-user weights. Users must repeatedl

26 May 2026

How does Bayesian Sampling help Membership Inference Attacks?

arXiv:2503.07482v2 Announce Type: replace-cross Abstract: Membership Inference Attacks (MIAs) aim to estimate whether a specific data point was used in the training of a given model. Existing state-of

26 May 2026

Applications

Hypothesis Generation and Inductive Inference in Children and Language Models

arXiv:2605.24528v1 Announce Type: new Abstract: Real world decision-making requires constructing mental models under uncertainty over evidence, over the underlying causal rules, and over the state of

applicationsarxiv-cs-ai

26 May 2026

Robust Counterfactual Inference in Markov Decision Processes

arXiv:2502.13731v5 Announce Type: replace Abstract: This paper addresses a key limitation in existing counterfactual inference methods for Markov Decision Processes (MDPs). Current approaches assume a

25 May 2026

What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference

arXiv:2605.23158v1 Announce Type: cross Abstract: The deployment of large language models (LLMs) on resource-constrained devices remains challenging, spurring interest in split inference, where models

researcharxiv-cs-cl

25 May 2026

extit{BlockFormer} : Transformer-based inference from interaction maps

arXiv:2605.21617v1 Announce Type: new Abstract: Inference from interaction maps, such as centromere identification from genome-wide chromosome conformation capture techniques -- notably Hi-C -- can be

23 May 2026

Harnesses for Inference-Time Alignment over Execution Trajectories

arXiv:2605.21516v1 Announce Type: new Abstract: Harness engineering has emerged as an important inference-time technique for large language model (LLM) agents, aiming to improve long-term performance

23 May 2026

Quant.npu: Enabling Efficient Mobile NPU Inference for on-device LLMs via Fully Static Quantization

arXiv:2605.20295v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed on mobile devices, where Neural Processing Units (NPUs) necessitate fully static quantization for

local-aiarxiv-cs-lg

21 May 2026

SPHERICAL KV: Angle-Domain Attention and Rate-Distortion Retention for Efficient Long-Context Inference

arXiv:2605.18856v1 Announce Type: cross Abstract: Long-context inference is increasingly constrained by the KV cache: resident memory grows with context length, and decoding becomes limited by repeate

researcharxiv-cs-cl

20 May 2026

Charon: A Unified and Fine-Grained Simulator for Large-Scale LLM Training and Inference

arXiv:2605.17164v1 Announce Type: cross Abstract: Deploying large-scale LLM training and inference with optimal performance is exceptionally challenging due to a complex design space of parallelism st

hardwarearxiv-cs-ai

Geometric Scaling of Bayesian Inference in LLMs

arXiv:2512.23752v5 Announce Type: replace-cross Abstract: Recent work has shown that small transformers trained in controlled 'wind-tunnel'' settings can implement exact Bayesian inference, and that t

Agents

Goal inference with Rao-Blackwellized Particle Filters

arXiv:2512.09269v2 Announce Type: replace Abstract: Inferring the eventual goal of a mobile agent from noisy observations of its trajectory is a fundamental estimation problem. We initiate the study o

agentsarxiv-cs-lg

Inference-Time Diversity in RL-Trained Lean Theorem Provers: A Diagnostic Study

arXiv:2601.16172v2 Announce Type: replace Abstract: RL-trained Lean theorem provers mode-collapse at inference time: on miniF2F-test with DeepSeek-Prover-V1.5-RL, doubling the i.i.d. sampling budget f

Lightweight Gaussian Process Inference in C++ on Metal and CUDA

arXiv:2605.17898v1 Announce Type: new Abstract: Gaussian process (GP) inference in Python is dominated by libraries such as GPyTorch and GPflow, which are built on deep-learning frameworks and inherit

hardwarearxiv-cs-lg

PACE: Geometry-Aware Bridge Transport for Single-Cell Trajectory Inference

arXiv:2605.18587v1 Announce Type: cross Abstract: Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor contin

Quantum Sidecar Architectures for Hybrid AI Training and Inference: Stateful Protected Registers, Stateless Reset-and-Reprepare Circuits and Quantum Weight-State Outlook

arXiv:2605.18031v1 Announce Type: cross Abstract: We propose a quantum sidecar architecture family for future hybrid AI training and inference. The central idea is not to store an entire Transformer i

TaskGround: Structured Executable Task Inference for Full-Scene Household Reasoning

arXiv:2605.18109v1 Announce Type: new Abstract: In real home deployments, household agents must often operate from a complete household scene and a situated household request, rather than from a clean