Search: “inference”

Requests of a Feather Must Flock Together: Batch Size vs. Prefix Homogeneity in LLM Inference

arXiv:2605.06046v2 Announce Type: replace Abstract: Auto-regressive token generation in large language models is memory-bound because it requires 'attending to' key and value tensors (KV cache) of all

local-aiarxiv-cs-lg

14 Oct 2026

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SCOPE Before You Sample: Conformal Scores Guide Posterior Exploration for Fast and Calibrated Bayesian Predictive Inference

DGX agent

arXiv:2610.17146v1 Announce Type: cross Abstract: Bayesian predictive regions account for parameter uncertainty but can be poorly calibrated under model misspecification, even with expensive full MCMC

model-releasesarxiv-cs-lg

14 Oct 2026

Selective Inference for Clustering Under Unknown Covariance

arXiv:2610.17458v1 Announce Type: cross Abstract: Unsupervised clustering is widely used to discover underlying group structure, after which researchers often seek to validate these groups via post-ho

14 Oct 2026

How Well Do Prior-Data Fitted Networks Amortize Bayesian Inference?

arXiv:2610.13764v1 Announce Type: cross Abstract: Prior-data fitted networks (PFNs) are trained to approximate the Bayesian posterior predictive distribution (PPD) of a synthetic prior, yet results ab

MHR-Router: Multimodal Heterogeneous Retrieval-Enhanced Adaptive Routing for VLM Inference

arXiv:2610.13278v1 Announce Type: new Abstract: Vision-language models (VLMs) exhibit complementary capabilities, yet selecting the most suitable expert for a given image-question query remains challe

Scalable Sparse Autoregressive Variational Inference for Non-Gaussian Spatial Fields

arXiv:2610.13656v1 Announce Type: cross Abstract: Latent field models are essential for spatial statistics, but the posterior distribution of the latent field, even with a Gaussian process (GP) prior,

Scan-Parallel Variational Inference for event-driven Latent Jump Models

arXiv:2610.12986v1 Announce Type: cross Abstract: Continuous-time latent state-space models are widely used for irregularly observed time series, typically representing uncertainty through a random in

Tutorials

Controllable Exaggeration for Generative Motion Models via Training-Time Adaptation and Inference-Time Guidance

arXiv:2610.12316v1 Announce Type: new Abstract: Recent motion generative models have demonstrated strong capabilities in synthesizing physically plausible character motion, but often overlook establis

tutorialsarxiv-cs-cv

9 Oct 2026

Closed-Form Noise Calibration Against Membership Inference for Random-Allocation DP-SGD

arXiv:2610.09651v1 Announce Type: new Abstract: DP-SGD protects training data by adding Gaussian noise to clipped gradients. The amount of noise is usually chosen by running a numerical privacy accoun

8 Oct 2026

Readout Stability in Prefill-Only Decision Models:Zero-Label Prediction and Inference-Time Compute Allocation

arXiv:2610.07716v1 Announce Type: new Abstract: Prefill-only decision models inspired by the Jev model score every candidate in a menu during a single forward pass and never decode, which makes one ca

researcharxiv-cs-cl

7 Oct 2026

VALSE: Vertical Adaptive Layer Skipping for Efficient Inference in Large Language Models

arXiv:2610.07606v1 Announce Type: new Abstract: This paper establishes a theoretical framework for vertical adaptive layer skipping, proving three foundational results: (i) an Expected FLOPs formula (

researcharxiv-cs-ai

7 Oct 2026

Where Do Two Populations of Persistence Diagrams Differ? Calibrated Local Inference at a Fixed Budget

model-releasesarxiv-cs-lg

arXiv:2610.08292v1 Announce Type: cross Abstract: Many two-sample tests for populations of persistence diagrams assess global differences without identifying the regions of the birth-death plane that

7 Oct 2026

Amortized Structured Stochastic Variational Inference for Gaussian Process Latent Variable Models

arXiv:2610.03647v1 Announce Type: cross Abstract: Many machine learning methods aim to approximate the lower-dimensional manifold on which the data lives. A desirable feature of such methods is that t

5 Oct 2026

BitNest: Bit-Nested Speculative Decoding for Memory-Efficient LLM Inference Acceleration

arXiv:2610.02800v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive generation by using a lightweight draft to propose multiple tokens for parallel verification. However, e

5 Oct 2026

Explainable Molecular Structure Inference from GC--MS with Diffusion Models and LLM Reranking

arXiv:2610.03066v1 Announce Type: cross Abstract: GC--EI--MS is an important technique for analyzing volatile and semivolatile compounds in complex samples. However, conventional methods rely heavily

5 Oct 2026

Before It Fades: Reinforcing Temporal Representations at Inference Time in VideoLLMs

arXiv:2610.01595v1 Announce Type: cross Abstract: Video Large Language Models (VideoLLMs) receive frames in sequential order and interpret how visual content evolves along the temporal axis, yet tempo

researcharxiv-cs-ai

2 Oct 2026

JevSpawn: Adaptive Agentic Inference through Compositional Action Spaces

arXiv:2610.00437v1 Announce Type: new Abstract: LLM agents generate intermediate reasoning and actions token by token, making extended interactions slow and computationally expensive. Jev-style models

2 Oct 2026

Symmetry Discovery in Quantum Learning: Observable-Level and Task-Level Inference from Finite Measurements

arXiv:2610.00157v1 Announce Type: cross Abstract: Symmetry reduces the capacity of a quantum learning model, but the imposed group must match both the measured information and the label transformation

safetyarxiv-cs-lg

2 Oct 2026

Demographic Pluralism: Inference-Time Modeling of Pluralistic Human Preference Distributions

arXiv:2609.38555v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in culturally sensitive settings, where alignment requires representing diverse preferences within po

safetyarxiv-cs-ai

1 Oct 2026

Constitutional adapters: Inference-time interventions for misalignment and misuse

arXiv:2609.36657v1 Announce Type: cross Abstract: Training models to act in accordance with an explicitly defined set of principles, or 'constitution,' has shown promise as a robust and transparent me

safetyarxiv-cs-ai

How to Run Statistics over LLM Judges and Trust the Results: Calibrated Inference for Small-Sample AI Evaluation with evalstats

arXiv:2609.35815v1 Announce Type: cross Abstract: Researchers across academia increasingly base significance claims on LLM judge scores and small-sample AI evaluations. Yet without well-calibrated con

safetyarxiv-cs-ai

ImbalancE: Inference-Time Latent Search Against Degree Imbalance in Link Prediction

arXiv:2609.36996v1 Announce Type: new Abstract: Knowledge Graph Embedding models have been extensively used to learn representations of entities and relations in Knowledge Graphs for predicting missin

Latent Inference-Time Guidance of Time Series Foundation Models

arXiv:2609.38058v1 Announce Type: cross Abstract: Time Series Foundation Models (TSFMs) currently provide state-of-the-art results in forecasting tasks. They are available out-of-the-box and rely on i

Mirror-Score: Calibrated, Inference-only Scoring Exposes the Limits of Sequence-compatibility Ranking in D-peptide Design

arXiv:2609.36057v1 Announce Type: new Abstract: D-peptides combine protease resistance with high target specificity, but computational design of D-peptide binders remains immature. Mirror-Peptidizer i

SCOPE: Observation-Conditioned Full-Target Prediction for Sparse PDE Inference

arXiv:2609.36527v2 Announce Type: new Abstract: Recovering complete physical fields from sparse observations is challenging because the measurements may not uniquely determine the underlying state. Di

The Geometry of Inference in Transformer Residual Streams

arXiv:2609.37824v1 Announce Type: new Abstract: Transformer language models build predictions through successive residual updates, but how their representations become specific to an eventual outcome

safetyarxiv-cs-cl

Thinking Before Thinking: Scaling Agentic Inference Through Meta-Reasoning

arXiv:2609.38147v1 Announce Type: new Abstract: As agents take on longer and more complex problems, controlling the execution becomes a task in its own right. Each step in the run brings new control c

Tutorials

UNBIND: UNlearning By INference-time Directional Steering for Code LLMs

arXiv:2609.35913v1 Announce Type: cross Abstract: Code large language models acquire programming capabilities from large code corpora, but can also memorize implementations that later require removal.

tutorialsarxiv-cs-ai

Leaky Students: Membership Inference against On-Policy Distillation

arXiv:2609.33136v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student to match a teacher's next-token distributions on student-generated trajectories. However, privileged infor

safetyarxiv-cs-lg

MaskCoFT: Masked Co-Adaptive Fine-Tuning for Memory-Efficient MoE Inference

model-releasesarxiv-cs-lg

arXiv:2609.34077v1 Announce Type: new Abstract: Mixture-of-experts (MoE) language models often exceed the memory of a single GPU. Expert offloading keeps most experts in host memory and loads them on

MiCo: Mutual Information Coverage Optimization through Semantic Erasure Modeling for Efficient MLLM Inference

arXiv:2609.34330v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated impressive performance in multimodal understanding, but processing large numbers of visual to

researcharxiv-cs-cv

One Sequence, Many Decodings: CAGenMol-2 Recasts Drug Design as Masked Molecular Inference

arXiv:2609.34301v1 Announce Type: new Abstract: Drug design couples property evaluation, conditional generation, structure-based design, and local optimization, yet machine learning systems typically

local-aiarxiv-cs-lg

RIDE: Reference-Anchored Inference-Time Diffusion Editing for Scaffold Hopping

arXiv:2609.35623v1 Announce Type: cross Abstract: Scaffold hopping is a critical task in drug discovery, which seeks to discover new, structurally distinct molecules that share key functional groups a

Safety-Constrained Cascade Inference for Robust Malaria Cell Classification Under Field Corruptions

arXiv:2609.33005v1 Announce Type: new Abstract: Automated malaria diagnosis from thin blood-smear microscopy could meaningfully reduce the burden on under-resourced laboratories, but a model that maxi

safetyarxiv-cs-cv

Sol-H3: Recursive Self-Improvement for MiniMax-H3 Inference Acceleration on Sol-Engine across Cloud and Edge

arXiv:2609.35110v1 Announce Type: cross Abstract: Video diffusion models are rapidly scaling and exhibiting enhanced generation capabilities. Among these recent advancements, MiniMax-H3 stands out as

local-aiarxiv-cs-cv

Statistical Testing for Multiple Instance Learning via Selective Inference with Applications to Computational Pathology

arXiv:2609.31712v1 Announce Type: new Abstract: Multiple instance learning (MIL) is widely used in computational pathology because it enables weakly supervised analysis of whole-slide images (WSIs) wi

researcharxiv-cs-cv

Steer2Grasp: Inference-Time Embodiment-Aware Steering for Diverse Physically Feasible Grasp Diffusion

arXiv:2609.33546v1 Announce Type: new Abstract: Current grasp diffusion models provide rich priors for generation, yet their object-centric approach can violate the kinematic and collision constraints

local-aiarxiv-cs-ro

Adaptive multi-resolution Gaussian processes: Scalable exact inference with naturally data-sparse covariance matrices

arXiv:2609.30348v1 Announce Type: cross Abstract: Gaussian processes constitute a cornerstone of probabilistic machine learning, yet scaling them to large datasets typically forces a trade-off between

researcharxiv-cs-ai

Inference-Time Target Speaker Unlearning in LLM-Based Automatic Speech Recognition

arXiv:2609.30439v1 Announce Type: new Abstract: We introduce target-speaker unlearning ASR (TSU-ASR) task in a fully end-to-end framework for multi-speaker ASR and diarization. Given a multi-speaker u

researcharxiv-cs-cl

LUCID: Learning Under Confounding for Inference and Discovery in Time Series

model-releasesarxiv-cs-lg

arXiv:2609.31315v1 Announce Type: new Abstract: Unobserved common causes are pervasive in real-world time series and can induce spurious associations that causal discovery methods mistake for direct e

Modeling Student Sensemaking with LLMs and Knowledge-Graph-Guided Inference

arXiv:2609.31046v1 Announce Type: new Abstract: Collaborative science learning requires nuanced interpretation of student dialogue to characterize how learners identify knowledge gaps, build explanati

researcharxiv-cs-cl

Agents

Graph-Based Inference and Topology-Aware Multi-Agent Reinforcement Learning for Large-Scale Railway Network Management

arXiv:2609.30150v1 Announce Type: new Abstract: Modern infrastructure asset management constitutes a complex sequential decision-making problem, characterized by long planning horizons and system-leve

agentsarxiv-cs-lg

25 Sept 2026

MemGuard-Alpha: Limits of Membership Inference for Detecting and Filtering Memorization-Contaminated Signals in LLM-Based Financial Forecasting

arXiv:2603.26797v2 Announce Type: replace Abstract: Large language models are increasingly used to generate financial alpha signals, but many have memorized the historical data in their training corpo

25 Sept 2026

Selective Inference for Deep Clustering in Latent Spaces

arXiv:2609.28756v1 Announce Type: cross Abstract: Deep clustering is a powerful approach for discovering meaningful structures in high-dimensional data by learning a low-dimensional latent representat

safetyarxiv-cs-lg

25 Sept 2026

Tutorials

Active Learning for Biodiversity Monitoring: From Label Efficiency to Reliable Ecological Inference

arXiv:2609.27409v1 Announce Type: new Abstract: Limited expert annotation capacity is a pervasive constraint in biodiversity monitoring. Passive acoustic recorders and camera traps generate data faste

tutorialsarxiv-cs-lg

FLINT: Fast Lightweight Inference for Traversability

arXiv:2609.26857v1 Announce Type: cross Abstract: Navigation in off-road conditions is challenging due to the lack of structure. There is no fixed vocabulary for what is traversable. The traversabilit

HINT-Blimp: Human INTent Inference from Multimodal Cues for Robotic Blimps

arXiv:2609.27154v1 Announce Type: new Abstract: In human-robot interaction, traditional interfaces such as joysticks and handheld tablets introduce latency into navigation tasks and require the operat

researcharxiv-cs-ro

MINER: Multi-crop INference-time Enhancement for Rare-Object Retrieval with Frozen Dual Encoders

model-releasesarxiv-cs-cv

arXiv:2609.27142v1 Announce Type: new Abstract: Text-to-image retrieval with frozen dual encoders degrades when the query names a small, visually subordinate object in a cluttered scene: a single glob