Search: “inference”

CoFEE: Reasoning Control for LLM-Based Feature Discovery

arXiv:2604.21584v1 Announce Type: new Abstract: Feature discovery from complex unstructured data is fundamentally a reasoning problem: it requires identifying abstractions that are predictive of a tar

Applications

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Cross-Domain Data Selection and Augmentation for Automatic Compliance Detection

DGX agent

arXiv:2604.21469v1 Announce Type: new Abstract: Automating the detection of regulatory compliance remains a challenging task due to the complexity and variability of legal texts. Models trained on one

applicationsarxiv-cs-cl

24 Apr 2026

Data-Driven Open-Loop Simulation for Digital-Twin Operator Decision Support in Wastewater Treatment

arXiv:2604.20935v1 Announce Type: cross Abstract: Wastewater treatment plants (WWTPs) need digital-twin-style decision support tools that can simulate plant response under prescribed control plans, to

Enhancing Online Recruitment with Category-Aware MoE and LLM-based Data Augmentation

arXiv:2604.21264v1 Announce Type: new Abstract: Person-Job Fit (PJF) is a critical component for online recruitment. Existing approaches face several challenges, particularly in handling low-quality j

Flow Matching for Conditional MRI-CT and CBCT-CT Image Synthesis

arXiv:2510.04823v2 Announce Type: replace Abstract: Generating synthetic CT (sCT) from MRI or CBCT plays a crucial role in enabling MRI-only and CBCT-based adaptive radiotherapy, improving treatment p

Focus on What Matters: Fisher-Guided Adaptive Multimodal Fusion for Vulnerability Detection

arXiv:2601.02438v3 Announce Type: replace-cross Abstract: Software vulnerability detection can be formulated as a binary classification problem that determines whether a given code snippet contains se

Hardware

GraphLeap: Decoupling Graph Construction and Convolution for Vision GNN Acceleration on FPGA

arXiv:2604.21290v1 Announce Type: new Abstract: Vision Graph Neural Networks (ViGs) represent an image as a graph of patch tokens, enabling adaptive, feature-driven neighborhoods. Unlike CNNs with fix

hardwarearxiv-cs-cv

HHL with a Coherent Fourier Oracle: A Proof-of-Concept Quantum Architecture for Joint Melody-Harmony Generation

arXiv:2604.20882v1 Announce Type: cross Abstract: Quantum algorithms with a proven theoretical speedup over classical computation are rare. Among the most prominent is the Harrow-Hassidim-Lloyd (HHL)

Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation

arXiv:2410.16698v2 Announce Type: replace Abstract: Dimensionality reduction (DR) offers a useful representation of complex high-dimensional data. Recent DR methods focus on hyperbolic geometry to der

researcharxiv-cs-lg

Hyperloop Transformers

model-releasesarxiv-cs-cl

arXiv:2604.21254v1 Announce Type: cross Abstract: LLM architecture research generally aims to maximize model quality subject to fixed compute/latency budgets. However, many applications of interest su

ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming

model-releasesarxiv-cs-lg

arXiv:2505.05261v3 Announce Type: replace-cross Abstract: Two-stage stochastic programming (2SP) offers a basic framework for modelling decision-making under uncertainty, yet scalability remains a cha

Language as a Latent Variable for Reasoning Optimization

model-releasesarxiv-cs-cl

arXiv:2604.21593v1 Announce Type: new Abstract: As LLMs reduce English-centric bias, a surprising trend emerges: non-English responses sometimes outperform English on reasoning tasks. We hypothesize t

Local Ai

Learning Reasoning Reward Models from Expert Demonstration via Inverse Reinforcement Learning

arXiv:2510.01857v3 Announce Type: replace Abstract: Current approaches to improving reasoning in large language models (LLMs) primarily rely on either supervised fine-tuning (SFT) over expert traces o

local-aiarxiv-cs-ai

Learning to Communicate: Toward End-to-End Optimization of Multi-Agent Language Systems

arXiv:2604.21794v1 Announce Type: new Abstract: Multi-agent systems built on large language models have shown strong performance on complex reasoning tasks, yet most work focuses on agent roles and or

Losing our Tail, Again: (Un)Natural Selection & Multilingual LLMs

arXiv:2507.03933v3 Announce Type: replace Abstract: Multilingual Large Language Models considerably changed how technologies influence language. While previous technologies could mediate or assist hum

researcharxiv-cs-cl

MaskDiME: Adaptive Masked Diffusion for Precise and Efficient Visual Counterfactual Explanations

arXiv:2602.18792v3 Announce Type: replace Abstract: Visual counterfactual explanations aim to reveal the minimal semantic modifications that can alter a model's prediction, providing causal and interp

Local Ai

Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding

arXiv:2604.21268v1 Announce Type: cross Abstract: Graphical User Interface (GUI) grounding requires mapping natural language instructions to precise pixel coordinates. However, due to visually homogen

local-aiarxiv-cs-ai

Agents

Multimodal Bayesian Network for Robust Assessment of Casualties in Autonomous Triage

arXiv:2512.18908v2 Announce Type: replace Abstract: Mass Casualty Incidents can overwhelm emergency medical systems and resulting delays or errors in the assessment of casualties can lead to preventab

agentsarxiv-cs-ai

Neural surrogates for crystal growth dynamics with variable supersaturation: explicit vs. implicit conditioning

model-releasesarxiv-cs-lg

arXiv:2604.21753v1 Announce Type: cross Abstract: Simulations of crystal growth are performed by using Convolutional Recurrent Neural Network surrogate models, trained on a dataset of time sequences c

Neuro-Symbolic Manipulation Understanding with Enriched Semantic Event Chains

arXiv:2604.21053v1 Announce Type: cross Abstract: Robotic systems operating in human environments must reason about how object interactions evolve over time, which actions are currently being performe

researcharxiv-cs-cv

PAT3D: Physics-Augmented Text-to-3D Scene Generation

arXiv:2511.21978v2 Announce Type: replace Abstract: We introduce PAT3D, the first physics-augmented text-to-3D scene generation framework that integrates vision-language models with physics-based simu

researcharxiv-cs-cv

Preserving Decision Sovereignty in Military AI: A Trade-Secret-Safe Architectural Framework for Model Replaceability, Human Authority, and State Control

arXiv:2604.20867v1 Announce Type: cross Abstract: Recent events surrounding the relationship between frontier AI suppliers and national-security customers have made a structural problem newly visible:

safetyarxiv-cs-ai

Tutorials

PrismaDV: Automated Task-Aware Data Unit Test Generation

arXiv:2604.21765v1 Announce Type: new Abstract: Data is a central resource for modern enterprises, and data validation is essential for ensuring the reliability of downstream applications. However, ex

tutorialsarxiv-cs-lg

RailVQA: A Benchmark and Framework for Efficient Interpretable Visual Cognition in Automatic Train Operation

arXiv:2603.27112v2 Announce Type: replace Abstract: As Automatic Train Operation (ATO) advances toward GoA4 and beyond, it increasingly depends on efficient, reliable cab-view visual perception and de

Ramen: Robust Test-Time Adaptation of Vision-Language Models with Active Sample Selection

arXiv:2604.21728v1 Announce Type: new Abstract: Pretrained vision-language models such as CLIP exhibit strong zero-shot generalization but remain sensitive to distribution shifts. Test-time adaptation

safetyarxiv-cs-cv

Reinforcing privacy reasoning in LLMs via normative simulacra from fiction

arXiv:2604.20904v1 Announce Type: cross Abstract: Information handling practices of LLM agents are broadly misaligned with the contextual privacy expectations of their users. Contextual Integrity (CI)

RewardBench 2: Advancing Reward Model Evaluation

model-releasesarxiv-cs-cl

arXiv:2506.01937v2 Announce Type: replace Abstract: Reward models are used throughout the post-training of language models to capture nuanced signals from preference data and provide a training target

SCASeg: Strip Cross-Attention for Efficient Semantic Segmentation

arXiv:2411.17061v2 Announce Type: replace Abstract: The Vision Transformer (ViT) has achieved notable success in computer vision, with its variants widely validated across various downstream tasks, in

Separable Expert Architecture: Toward Privacy-Preserving LLM Personalization via Composable Adapters and Deletable User Proxies

arXiv:2604.21571v1 Announce Type: new Abstract: Current model training approaches incorporate user information directly into shared weights, making individual data removal computationally infeasible w

Serialisation Strategy Matters: How FHIR Data Format Affects LLM Medication Reconciliation

arXiv:2604.21076v1 Announce Type: cross Abstract: Medication reconciliation at clinical handoffs is a high-stakes, error-prone process. Large language models are increasingly proposed to assist with t

Spatial Metaphors for LLM Memory: A Critical Analysis of the MemPalace Architecture

arXiv:2604.21284v1 Announce Type: new Abstract: MemPalace is an open-source AI memory system that applies the ancient method of loci (memory palace) spatial metaphor to organize long-term memory for l

Agents

SpatiO: Adaptive Test-Time Orchestration of Vision-Language Agents for Spatial Reasoning

arXiv:2604.21190v1 Announce Type: new Abstract: Understanding visual scenes requires not only recognizing objects but also reasoning about their spatial relationships. Unlike general vision-language t

agentsarxiv-cs-cv

Agents

Speculative Actions: A Lossless Framework for Faster Agentic Systems

arXiv:2510.04371v2 Announce Type: replace Abstract: AI agents are increasingly deployed in complex, interactive environments, yet their runtime remains a major bottleneck for training, evaluation, and

agentsarxiv-cs-ai

Local Ai

Teacher-Guided Routing for Sparse Vision Mixture-of-Experts

arXiv:2604.21330v1 Announce Type: new Abstract: Recent progress in deep learning has been driven by increasingly large-scale models, but the resulting computational cost has become a critical bottlene

local-aiarxiv-cs-cv

Tempered Sequential Monte Carlo for Trajectory and Policy Optimization with Differentiable Dynamics

arXiv:2604.21456v1 Announce Type: new Abstract: We propose a sampling-based framework for finite-horizon trajectory and policy optimization under differentiable dynamics by casting controller design a

safetyarxiv-cs-lg

Ternary Memristive Logic: Hardware for Reasoning Realized via Domain Algebra

arXiv:2604.20891v1 Announce Type: cross Abstract: Memristive crossbars store numerical weights needing aggregation and decoding; a single junction means nothing alone. This paper presents a fundamenta

The Path Not Taken: Duality in Reasoning about Program Execution

arXiv:2604.20917v1 Announce Type: cross Abstract: Large language models (LLMs) have shown remarkable capabilities across diverse coding tasks. However, their adoption requires a true understanding of

The Recurrent Transformer: Greater Effective Depth and Efficient Decoding

model-releasesarxiv-cs-lg

arXiv:2604.21215v1 Announce Type: new Abstract: Transformers process tokens in parallel but are temporally shallow: at position t, each layer attends to key-value pairs computed based on the previous

Thinking Like a Botanist: Challenging Multimodal Language Models with Intent-Driven Chain-of-Inquiry

arXiv:2604.20983v1 Announce Type: cross Abstract: Vision evaluations are typically done through multi-step processes. In most contemporary fields, experts analyze images using structured, evidence-bas

Tutorials

Thinking with Reasoning Skills: Fewer Tokens, More Accuracy

arXiv:2604.21764v1 Announce Type: new Abstract: Reasoning LLMs often spend substantial tokens on long intermediate reasoning traces (e.g., chain-of-thought) when solving new problems. We propose to su

tutorialsarxiv-cs-ai

TimePre: Bridging Accuracy, Efficiency, and Stability in Probabilistic Time-Series Forecasting

arXiv:2511.18539v2 Announce Type: replace-cross Abstract: We propose TimePre, a simple framework that unifies the efficiency of Multilayer Perceptron (MLP)-based models with the distributional flexibi

Tutorials

Transferable Physics-Informed Representations via Closed-Form Head Adaptation

arXiv:2604.21761v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have garnered significant interest for their potential in solving partial differential equations (PDEs) that go

tutorialsarxiv-cs-lg

Tuning for TraceTarnish: Techniques, Trends, and Testing Tangible Traits

arXiv:2512.03465v3 Announce Type: replace-cross Abstract: In this study, we more rigorously evaluated our attack script extit{TraceTarnish}, which leverages adversarial stylometry principles to anonym

researcharxiv-cs-cl

Unlocking Multi-Spectral Data for Multi-Modal Models with Guided Inputs and Chain-of-Thought Reasoning

arXiv:2604.21032v1 Announce Type: new Abstract: Multi-spectral imagery is a valuable input signal for Remote Sensing applications, such as land-use and land-cover classification and environmental moni

Applications

Vista4D: Video Reshooting with 4D Point Clouds

arXiv:2604.21915v1 Announce Type: new Abstract: We present Vista4D, a robust and flexible video reshooting framework that grounds the input video and target cameras in a 4D point cloud. Specifically,

applicationsarxiv-cs-cv

VLA-Forget: Vision-Language-Action Unlearning for Embodied Foundation Models

arXiv:2604.03956v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models are emerging as embodied foundation models for robotic manipulation, but their deployment introduces a new

safetyarxiv-cs-ai

A Hough transform approach to safety-aware scalar field mapping using Gaussian Processes

arXiv:2604.20799v1 Announce Type: new Abstract: This paper presents a framework for mapping unknown scalar fields using a sensor-equipped autonomous robot operating in unsafe environments. The unsafe

safetyarxiv-cs-ro

23 Apr 2026

A Survey of Scaling in Large Language Model Reasoning