Search: “inference”

The Hidden Signal of Verifier Strictness: Controlling and Improving Step-Wise Verification via Selective Latent Steering

arXiv:2605.20745v1 Announce Type: cross Abstract: Generative verifiers have emerged as a promising paradigm for step-wise verification, but their verification behavior is often poorly calibrated: they

researcharxiv-cs-cl

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Model Releases

The Visual Iconicity Challenge: Evaluating Vision-Language Models on Sign Language Form-Meaning Mapping

DGX agent

arXiv:2510.08482v3 Announce Type: replace-cross Abstract: Iconicity, the resemblance between linguistic form and meaning, is pervasive in signed languages, offering a natural testbed for visual ground

model-releasesarxiv-cs-cl

21 May 2026

TreeText-CTS: Compact, Source-Traceable Tree-Path Evidence for Irregular Clinical Time-Series Prediction

arXiv:2605.20292v1 Announce Type: new Abstract: Numerical time-series models can effectively process irregular electronic health record (EHR) trajectories, but they do not naturally expose the measure

researcharxiv-cs-lg

Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs

model-releasesarxiv-cs-cl

arXiv:2505.19075v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated remarkable general capabilities, but enhancing skills such as reasoning often demands substanti

v0.30.0-rc22

v0.30.0-rc22 is a pre-release version of Ollama that changes the architecture to directly support llama.cpp instead of building on top of GGML, and allows for compatibility with GGUF file format. MLX

local-aiollama-releases

Velocityformer: Broken-Symmetry-Matched Equivariant Graph Transformers for Cosmological Velocity Reconstruction

arXiv:2605.21483v1 Announce Type: cross Abstract: Precise measurement of the kinematic Sunyaev-Zel'dovich (kSZ) effect - a probe of the large-scale distribution of baryonic matter, a key observable fo

safetyarxiv-cs-lg

Agents

What if Agents Could Imagine? Reinforcing Open-Vocabulary HOI Comprehension through Generation

arXiv:2602.11499v2 Announce Type: replace Abstract: Multimodal Large Language Models have shown promising capabilities in bridging visual and textual reasoning, yet their reasoning capabilities in Ope

agentsarxiv-cs-cv

WildRoadBench: A Wild Aerial Road-Damage Grounding Benchmark for Vision-Language Models and Autonomous Agents

model-releasesarxiv-cs-cv

arXiv:2605.20306v1 Announce Type: new Abstract: We introduce WildRoadBench, a wild aerial road-damage grounding benchmark that couples direct visual grounding by vision-language models with autonomous

A Family of Divergence Measures for Evaluating the Reconstruction Quality of Explainable Ensemble Trees

arXiv:2605.19618v1 Announce Type: new Abstract: Validating interpretable surrogate models for ensemble learners requires measuring agreement between the ensemble's internal representation and its surr

Automatically Improving Simulation Physics for Articulated Objects

arXiv:2605.19136v1 Announce Type: new Abstract: Simulation is a central tool for scalable robot learning, but its effectiveness depends on the quality of object assets. While modern 3D datasets provid

safetyarxiv-cs-ro

b9239

local-aillama-cpp-releases

Build b9239 is a llama.cpp release that includes a fix for the --fit verbosity flag when used with --verbosity 4 . The release provides compiled binaries for multiple platforms including macOS (Apple

b9244

local-aillama-cpp-releases

b9244 is an intermediate build release of llama.cpp, a C/C++ implementation framework for running large language models with GGUF format support. The release includes pre-compiled binaries for multipl

Backtracking When It Strays: Mitigating Dual Exposure Biases in LLM Reasoning Distillation

arXiv:2605.19433v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable success in complex reasoning tasks via long chain-of-thought (CoT), yet their immense computatio

Boosting Text-to-Image Diffusion Models via Core Token Attention-Based Seed Selection

arXiv:2605.19532v1 Announce Type: new Abstract: Text-to-image diffusion models can synthesize high-quality images, yet the outcome is notoriously sensitive to the random seed: different initial seeds

safetyarxiv-cs-cv

BrainDyn: A Sheaf Neural ODE for Generative Brain Dynamics

arXiv:2605.19324v1 Announce Type: new Abstract: Efficient neural network models that generate brain-like dynamic activity can be a valuable resource for generating synthetic data, analyzing difference

researcharxiv-cs-lg

Industry

Build real-time voice applications with Amazon SageMaker AI and vLLM

Voice agents, live captioning, contact center analytics, and accessibility tools all depend on real-time speech-to-text, where your application streams audio in and receives transcription back simulta

industryaws-ml-blog

Tutorials

CANINE: Coaching Visually Impaired Users for Interactive Navigation with a Robot Guide Dog

arXiv:2605.19501v1 Announce Type: cross Abstract: Robot guide dogs offer navigation assistance that greatly expands the independent mobility of the visually impaired, but their effective use requires

tutorialsarxiv-cs-ai

Causal Evidence for Attention Head Imbalance in Modality Conflict Hallucination

model-releasesarxiv-cs-ai

arXiv:2605.19250v1 Announce Type: new Abstract: Modality-conflict hallucination occurs when multimodal large language models (MLLMs) prioritize erroneous textual premises over contradictory visual evi

Agents

CMAD: Cooperative Multi-Agent Diffusion via Stochastic Optimal Control

arXiv:2602.10933v2 Announce Type: replace Abstract: Continuous-time generative models have achieved remarkable success in image restoration and synthesis. However, controlling the composition of multi

agentsarxiv-cs-lg

Code-Guided Reasoning for Small Language Models: Evaluating Executable MCQA Scaffolds

arXiv:2605.18827v1 Announce Type: cross Abstract: Multiple-choice QA benchmarks usually evaluate small language models (SLMs) as direct answerers, but deployed language-model systems increasingly rely

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning

arXiv:2507.15698v2 Announce Type: replace-cross Abstract: Process Reward Models (PRMs) play a central role in evaluating and guiding multi-step reasoning in large language models (LLMs), especially fo

CompoSE: Compositional Synthesis and Editing of 3D Shapes via Part-Aware Control

arXiv:2605.19350v1 Announce Type: cross Abstract: Creating and editing high-quality 3D content remains a central challenge in computer graphics. We address this challenge by introducing CompoSE, a nov

CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning

arXiv:2605.20075v1 Announce Type: cross Abstract: Chain-of-thought (CoT) is a standard approach for eliciting reasoning capabilities from large language models (LLMs). However, the common CoT paradigm

D^3-Subsidy: Online and Sequential Driver Subsidy Decision-Making for Large-Scale Ride-Hailing Market

arXiv:2605.20036v1 Announce Type: new Abstract: Ride-hailing platforms like DiDi Chuxing operate in highly dynamic environments where balancing driver supply and passenger demand is critical. Although

Descriptive versus Regulatory Uncertainty in Bounded Predictive Systems

arXiv:2605.18909v1 Announce Type: new Abstract: Any system that models the world under finite representational capacity must compress; any compression entails a prior; and the prior is the system's bi

Disentangling generalization and memorization in large language models using chess

model-releasesarxiv-cs-ai

arXiv:2601.16823v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit remarkable capabilities, yet it remains unclear to what extent these reflect sophisticated recall or genu

Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection

arXiv:2605.19122v1 Announce Type: cross Abstract: Tensor-valued data arise naturally in neuroimaging, genomics, climate science, and spatiotemporal networks, where multilinear dependencies across mode

Dual-Gated Epistemic Time-Dilation: Autonomous Compute Modulation in Asynchronous MARL

arXiv:2603.23722v2 Announce Type: replace-cross Abstract: While Multi-Agent Reinforcement Learning (MARL) algorithms achieve unprecedented successes across complex continuous domains, their standard d

safetyarxiv-cs-lg

EmbGen: Teaching with Reassembled Corpora

arXiv:2605.19394v1 Announce Type: cross Abstract: Adapting small instruction-tuned models to specialized domains often relies on supervised fine-tuning (SFT) on curated instruction-response examples,

researcharxiv-cs-ai

EventPrune: Cascaded Event-Assisted Token Pruning for Efficient First-Person Dynamic Spatial Reasoning

model-releasesarxiv-cs-cv

arXiv:2605.19506v1 Announce Type: new Abstract: First-person dynamic spatial reasoning requires models to track continuous motion and precise geometric structure, but the quadratic attention cost of T

Applications

Exploiting Non-Negativity in DAG Structure Learning

arXiv:2605.19947v1 Announce Type: new Abstract: This work addresses the problem of learning directed acyclic graphs (DAGs) from nodal observations generated by a linear structural equation model. DAG

applicationsarxiv-cs-lg

Exposing Functional Fusion: A New Class of Strategic Backdoor in Dynamic Prompt Architectures

model-releasesarxiv-cs-cv

arXiv:2605.19478v1 Announce Type: cross Abstract: Existing ViT backdoor attacks based on backbone-overwriting full-tuning are computationally expensive and inflict performance degradation. This has fo

FedMental: Evaluating Federated Learning for Mental Health Detection from Social Media Data

model-releasesarxiv-cs-cl

arXiv:2605.18936v1 Announce Type: cross Abstract: Social media text data are often used to train Machine Learning (ML) models to identify users exhibiting high-risk mental health behaviors. However, s

FGSVQA: Frequency-Guided Short-form Video Quality Assessment

arXiv:2605.20016v1 Announce Type: cross Abstract: Short-form video poses new challenges to the quality assessment of user-generated content (UGC) due to its complex generation pipeline, rapid content

researcharxiv-cs-cv

FieldFormer: Locality-Aware Transformers for Spatio-Temporal Modeling on Sparse Sensor Networks

arXiv:2510.03589v2 Announce Type: replace Abstract: Spatio-temporal sensor data in real-world systems is often sparse, noisy, and irregular, making latent field reconstruction fundamentally underconst

FlowErase-RL: Rethinking Concept Erasure as Reward Optimization in Flow Matching Models

arXiv:2605.19739v1 Announce Type: new Abstract: Recent advances in flow matching models have significantly improved text-to-image generation quality, but also introduce growing safety risks due to the

safetyarxiv-cs-cv

Gaussian Approximation and Multiplier Bootstrap for Federated Linear Stochastic Approximation

arXiv:2605.19629v1 Announce Type: cross Abstract: In this paper, we establish Berry-Esseen-type bounds for federated linear stochastic approximation (LSA). Our results provide the first federated Gaus

GenAI-FDIA: Physics-Informed Generative Models for False Data Injection Attacks

arXiv:2605.18873v1 Announce Type: cross Abstract: Training and evaluating false data injection attack (FDIA) detectors for power systems is constrained by data scarcity. Operational grid measurements

researcharxiv-cs-ai

Generative Auto-Bidding with Unified Modeling and Exploration

arXiv:2605.19457v1 Announce Type: new Abstract: Automated bidding is central to modern digital advertising. Early rule-based methods lacked adaptability, while subsequent Reinforcement Learning approa

GOAL: Graph-based Objective-Aligned Diffusion Solvers for Dynamic Multi-Objective Optimization

arXiv:2605.19119v1 Announce Type: cross Abstract: Existing neural combinatorial optimization solvers frame solution search as imitation of optimal decisions, inherently limiting their utility to singl

researcharxiv-cs-ai

Graph Neural Planning and Predictive Control for Multi-Robot Communication-Constrained Unlabeled Motion Planning

arXiv:2605.19209v1 Announce Type: new Abstract: The multi-robot unlabeled motion planning problem of concurrently assigning robots to goals and generating safe trajectories is central in many collabor

safetyarxiv-cs-ro

Guiding Neuro-Symbolic Scenario Generation with Spatio-Temporal Logic

arXiv:2605.19038v1 Announce Type: cross Abstract: The rapid advancement of autonomous driving (AD) technologies has outpaced the development of robust safety evaluation methods. Conventional testing r

safetyarxiv-cs-lg

HeadRank: Decoding-Free Passage Reranking via Preference-Aligned Attention Heads

arXiv:2604.17237v2 Announce Type: replace-cross Abstract: Decoding-free reranking methods that read relevance signals directly from LLM attention weights offer significant latency advantages over auto

Hardware

Hyrax: An Extensible Framework for Rapid ML Experimentation and Unsupervised Discovery in the Era of Rubin, Roman, and Euclid

arXiv:2605.18959v1 Announce Type: cross Abstract: The NSF-DOE Vera C. Rubin Observatory, Roman Space Telescope, Euclid, and other next-generation surveys will deliver imaging, spectroscopic, and time-

hardwarearxiv-cs-lg

In-Context Learning Operates as Concept Subspace Learning

arXiv:2605.18830v1 Announce Type: new Abstract: Regression and Bayesian accounts of in-context learning (ICL) explain how demonstrations can induce predictors, while mechanistic analyses often identif

KG-ASG: Collision-Knowledge-Guided Closed-Loop Adversarial Scenario Generation With Primary-Support Attribution

arXiv:2605.18895v1 Announce Type: cross Abstract: Safety validation of autonomous driving systems requires high-risk scenario coverage, clear collision semantics, executable trajectories, and attribut

KIO-planner: Attention-Guided Single-Stage Motion Planning with Dual Mapping for UAV Navigation

arXiv:2605.19703v1 Announce Type: new Abstract: Autonomous UAV flight in confined, wall-dense environments requires low-latency and reliable motion planning under strict safety constraints. Traditiona

local-aiarxiv-cs-ro

Learning-Accelerated Optimization-based Trajectory Planning for Cooperative Aerial-Ground Handover Missions

arXiv:2605.19562v1 Announce Type: cross Abstract: This paper presents a learning-augmented trajectory planning framework for cooperative unmanned aerial vehicle (UAV) and unmanned ground vehicle (UGV)