Search: “inference”

Evaluating In-Context Translation with Synchronous Context-Free Grammar Transduction

arXiv:2604.07320v1 Announce Type: cross Abstract: Low-resource languages pose a challenge for machine translation with large language models (LLMs), which require large amounts of training data. One p

researcharxiv-cs-ai

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Research

Faithful-First Reasoning, Planning, and Acting for Multimodal LLMs

DGX agent

arXiv:2511.08409v4 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) frequently suffer from unfaithfulness, generating reasoning chains that drift from visual evidence or contr

researcharxiv-cs-ai

10 Apr 2026

Local Ai

Fast reconstruction-based ROI triggering via anomaly detection in the CYGNO optical TPC

arXiv:2512.24290v2 Announce Type: replace-cross Abstract: Optical-readout Time Projection Chambers (TPCs) produce megapixel-scale images whose fine-grained topological information is essential for rar

local-aiarxiv-cs-lg

Hardware

ForkKV: Scaling Multi-LoRA Agent Serving via Copy-on-Write Disaggregated KV Cache

arXiv:2604.06370v1 Announce Type: cross Abstract: The serving paradigm of large language models (LLMs) is rapidly shifting towards complex multi-agent workflows where specialized agents collaborate ov

hardwarearxiv-cs-lg

Hardware

Foundry: Template-Based CUDA Graph Context Materialization for Fast LLM Serving Cold Start

arXiv:2604.06664v1 Announce Type: cross Abstract: Modern LLM service providers increasingly rely on autoscaling and parallelism reconfiguration to respond to rapidly changing workloads, but cold-start

hardwarearxiv-cs-lg

From Classical Machine Learning to Tabular Foundation Models: An Empirical Investigation of Robustness and Scalability Under Class Imbalance in Emergency and Critical Care

arXiv:2512.21602v2 Announce Type: replace-cross Abstract: Millions of patients pass through emergency departments and intensive care units each year, where clinicians must make high-stakes decisions u

researcharxiv-cs-cv

From Ground Truth to Measurement: A Statistical Framework for Human Labeling

arXiv:2604.07591v1 Announce Type: cross Abstract: Supervised machine learning assumes that labeled data provide accurate measurements of the concepts models are meant to learn. Yet in practice, human

Governing frontier general-purpose AI in the public sector: adaptive risk management and policy capacity under uncertainty through 2030

arXiv:2604.06215v1 Announce Type: cross Abstract: The governance of frontier general-purpose artificial intelligence has become a public-sector problem of institutional design, not merely a technical

safetyarxiv-cs-ai

GraphWalker: Graph-Guided In-Context Learning for Clinical Reasoning on Electronic Health Records

arXiv:2604.06684v1 Announce Type: new Abstract: Clinical Reasoning on Electronic Health Records (EHRs) is a fundamental yet challenging task in modern healthcare. While in-context learning (ICL) offer

applicationsarxiv-cs-lg

HEX: Humanoid-Aligned Experts for Cross-Embodiment Whole-Body Manipulation

arXiv:2604.07993v1 Announce Type: new Abstract: Humans achieve complex manipulation through coordinated whole-body control, whereas most Vision-Language-Action (VLA) models treat robot body parts larg

applicationsarxiv-cs-ro

HiCI: Hierarchical Construction-Integration for Long-Context Attention

arXiv:2603.20843v2 Announce Type: replace Abstract: Long-context language modeling is commonly framed as a scalability challenge of token-level attention, yet local-to-global information structuring r

HiF-VLA: Hindsight, Insight and Foresight through Motion Representation for Vision-Language-Action Models

arXiv:2512.09928v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have recently enabled robotic manipulation by grounding visual and linguistic cues into actions. However, most V

applicationsarxiv-cs-ro

How Independent are Large Language Models? A Statistical Framework for Auditing Behavioral Entanglement and Reweighting Verifier Ensembles

arXiv:2604.07650v1 Announce Type: cross Abstract: The rapid growth of the large language model (LLM) ecosystem raises a critical question: are seemingly diverse models truly independent? Shared pretra

Tutorials

How to sketch a learning algorithm

arXiv:2604.07328v1 Announce Type: new Abstract: How does the choice of training data influence an AI model? This question is of central importance to interpretability, privacy, and basic science. At i

tutorialsarxiv-cs-lg

IatroBench: Pre-Registered Evidence of Iatrogenic Harm from AI Safety Measures

arXiv:2604.07709v1 Announce Type: cross Abstract: Ask a frontier model how to taper six milligrams of alprazolam (psychiatrist retired, ten days of pills left, abrupt cessation causes seizures) and it

In-Context Learning in Speech Language Models: Analyzing the Role of Acoustic Features, Linguistic Structure, and Induction Heads

arXiv:2604.06356v1 Announce Type: cross Abstract: In-Context Learning (ICL) has been extensively studied in text-only Language Models, but remains largely unexplored in the speech domain. Here, we inv

researcharxiv-cs-ai

Loop, Think, & Generalize: Implicit Reasoning in Recurrent-Depth Transformers

arXiv:2604.07822v1 Announce Type: new Abstract: We study implicit reasoning, i.e. the ability to combine knowledge or rules within a single forward pass. While transformer-based large language models

researcharxiv-cs-cl

Machine Unlearning in the Era of Quantum Machine Learning: An Empirical Study

arXiv:2512.19253v4 Announce Type: replace-cross Abstract: We present the first empirical study of machine unlearning (MU) in hybrid quantum-classical neural networks. While MU has been extensively exp

safetyarxiv-cs-ai

MedVR: Annotation-Free Medical Visual Reasoning via Agentic Reinforcement Learning

arXiv:2604.08203v1 Announce Type: new Abstract: Medical Vision-Language Models (VLMs) hold immense promise for complex clinical tasks, but their reasoning capabilities are often constrained by text-on

safetyarxiv-cs-cv

Local Ai

Mind the Generative Details: Direct Localized Detail Preference Optimization for Video Diffusion Models

arXiv:2601.04068v3 Announce Type: replace Abstract: Aligning text-to-video diffusion models with human preferences is crucial for generating high-quality videos. Existing Direct Preference Otimization

local-aiarxiv-cs-cv

Mitigating Visual Context Degradation in Large Multimodal Models: A Training-Free Decoupled Agentic Framework

model-releasesarxiv-cs-cv

arXiv:2509.23322v2 Announce Type: replace Abstract: With the continuous expansion of Large Language Models (LLMs) and advances in reinforcement learning, LLMs have demonstrated exceptional reasoning c

ModeX: Evaluator-Free Best-of-N Selection for Open-Ended Generation

arXiv:2601.02535v2 Announce Type: replace Abstract: Selecting a single high-quality output from multiple stochastic generations remains a fundamental challenge for large language models (LLMs), partic

MolmoWeb: Open Visual Web Agent and Open Data for the Open Web

arXiv:2604.08516v1 Announce Type: new Abstract: Web agents--autonomous systems that navigate and execute tasks on the web on behalf of users--have the potential to transform how people interact with t

agentsarxiv-cs-cv

Tutorials

MoRight: Motion Control Done Right

arXiv:2604.07348v1 Announce Type: cross Abstract: Generating motion-controlled videos--where user-specified actions drive physically plausible scene dynamics under freely chosen viewpoints--demands tw

tutorialsarxiv-cs-ai

MSG Score: Automated Video Verification for Reliable Multi-Scene Generation

arXiv:2411.19121v2 Announce Type: replace-cross Abstract: While text-to-video diffusion models have advanced significantly, creating coherent long-form content remains unreliable due to stochastic sam

applicationsarxiv-cs-ai

Multi-objective Evolutionary Merging Enables Efficient Reasoning Models

model-releasesarxiv-cs-ai

arXiv:2604.06465v1 Announce Type: cross Abstract: Reasoning models have demonstrated remarkable capabilities in solving complex problems by leveraging long chains of thought. However, this more delibe

NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed Autonomous Navigation

arXiv:2406.13086v2 Announce Type: replace Abstract: Lightweight autonomous unmanned aerial vehicles (UAV) are emerging as a central component of a broad range of applications. However, autonomous navi

agentsarxiv-cs-ro

Negative Binomial Variational Autoencoders for Overdispersed Latent Modeling

model-releasesarxiv-cs-lg

arXiv:2508.05423v2 Announce Type: replace Abstract: Although artificial neural networks are often described as brain-inspired, their representations typically rely on continuous activations, such as t

Neural Computers

arXiv:2604.06425v1 Announce Type: cross Abstract: We propose a new frontier: Neural Computers (NCs) -- an emerging machine form that unifies computation, memory, and I/O in a learned runtime state. Un

safetyarxiv-cs-ai

On Integrating Resilience and Human Oversight into LLM-Assisted Modeling Workflows for Digital Twins

model-releasesarxiv-cs-ai

arXiv:2603.25898v2 Announce Type: replace-cross Abstract: LLM-assisted modeling holds the potential to rapidly build executable Digital Twins of complex systems from only coarse descriptions and senso

Open-Ended Instruction Realization with LLM-Enabled Multi-Planner Scheduling in Autonomous Vehicles

model-releasesarxiv-cs-cv

arXiv:2604.08031v1 Announce Type: cross Abstract: Most Human-Machine Interaction (HMI) research overlooks the maneuvering needs of passengers in autonomous driving (AD). Natural language offers an int

ParkSense: Where Should a Delivery Driver Park? Leveraging Idle AV Compute and Vision-Language Models

arXiv:2604.07912v1 Announce Type: new Abstract: Finding parking consumes a disproportionate share of food delivery time, yet no system addresses precise parking-spot selection relative to merchant ent

agentsarxiv-cs-cv

PASK: Toward Intent-Aware Proactive Agents with Long-Term Memory

arXiv:2604.08000v1 Announce Type: cross Abstract: Proactivity is a core expectation for AGI. Prior work remains largely confined to laboratory settings, leaving a clear gap in real-world proactive age

PEER: Unified Process-Outcome Reinforcement Learning for Structured Empathetic Reasoning

arXiv:2508.09521v2 Announce Type: replace Abstract: Emotional support conversations require more than fluent responses. Supporters need to understand the seeker's situation and emotions, adopt an appr

ProofSketcher: Hybrid LLM + Lightweight Proof Checker for Reliable Math/Logic Reasoning

arXiv:2604.06401v1 Announce Type: new Abstract: The large language models (LLMs) might produce a persuasive argument within mathematical and logical fields, although such argument often includes some

researcharxiv-cs-ai

PULSE: Privileged Knowledge Transfer from Rich to Deployable Sensors for Embodied Multi-Sensory Learning

model-releasesarxiv-cs-ai

arXiv:2510.24058v2 Announce Type: replace-cross Abstract: Multi-sensory systems for embodied intelligence, from wearable body-sensor networks to instrumented robotic platforms, routinely face a sensor

Reasoning Within the Mind: Dynamic Multimodal Interleaving in Latent Space

arXiv:2512.12623v3 Announce Type: replace-cross Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have significantly enhanced cross-modal understanding and reasoning by incorpo

ReDAct: Uncertainty-Aware Deferral for LLM Agents

arXiv:2604.07036v1 Announce Type: cross Abstract: Recently, LLM-based agents have become increasingly popular across many applications, including complex sequential decision-making problems. However,

agentsarxiv-cs-lg

ReflectRM: Boosting Generative Reward Models via Self-Reflection within a Unified Judgment Framework

arXiv:2604.07506v1 Announce Type: cross Abstract: Reward Models (RMs) are critical components in the Reinforcement Learning from Human Feedback (RLHF) pipeline, directly determining the alignment qual

SealQA: Raising the Bar for Reasoning in Search-Augmented Language Models

arXiv:2506.01062v4 Announce Type: replace Abstract: We introduce SealQA, a new challenge benchmark for evaluating SEarch-Augmented Language models on fact-seeking questions where web search yields con

Sensitivity-Positional Co-Localization in GQA Transformers

arXiv:2604.07766v1 Announce Type: new Abstract: We investigate a fundamental structural question in Grouped Query Attention (GQA) transformers: do the layers most sensitive to task correctness coincid

Local Ai

SepSeq: A Training-Free Framework for Long Numerical Sequence Processing in LLMs

arXiv:2604.07737v1 Announce Type: new Abstract: While transformer-based Large Language Models (LLMs) theoretically support massive context windows, they suffer from severe performance degradation when

local-aiarxiv-cs-cl

SMPL-GPTexture: Dual-View 3D Human Texture Estimation using Text-to-Image Generation Models

arXiv:2504.13378v2 Announce Type: replace-cross Abstract: Generating high-quality, photorealistic textures for 3D human avatars remains a fundamental yet challenging task in computer vision and multim

safetyarxiv-cs-cv

Hardware

Splats under Pressure: Exploring Performance-Energy Trade-offs in Real-Time 3D Gaussian Splatting under Constrained GPU Budgets

arXiv:2604.07177v1 Announce Type: cross Abstract: We investigate the feasibility of real-time 3D Gaussian Splatting (3DGS) rasterisation on edge clients with varying Gaussian splat counts and GPU comp

hardwarearxiv-cs-lg

Squeeze Evolve: Unified Multi-Model Orchestration for Verifier-Free Evolution

arXiv:2604.07725v1 Announce Type: cross Abstract: We show that verifier-free evolution is bottlenecked by both diversity and efficiency: without external correction, repeated evolution accelerates col

researcharxiv-cs-cl

SSPINNpose: A Self-Supervised PINN for Inertial Pose and Dynamics Estimation

arXiv:2506.11786v2 Announce Type: replace Abstract: Accurate real-time estimation of human movement dynamics, including internal joint moments and muscle forces, is essential for applications in clini

applicationsarxiv-cs-lg

Stacked from One: Multi-Scale Self-Injection for Context Window Extension

arXiv:2603.04759v2 Announce Type: replace Abstract: The limited context window of contemporary large language models (LLMs) remains a primary bottleneck for their broader application across diverse do

Tutorials

Steering the Verifiability of Multimodal AI Hallucinations

arXiv:2604.06714v1 Announce Type: new Abstract: AI applications driven by multimodal large language models (MLLMs) are prone to hallucinations and pose considerable risks to human users. Crucially, su

tutorialsarxiv-cs-ai