Search: “inference”

Evaluating the Generalizability of Foundation Models for Extreme Environmental Events: Case Study of California Wildfire PM2.5

model-releasesarxiv-cs-lg

arXiv:2607.07951v1 Announce Type: new Abstract: Wildfire smoke events produce extreme PM_{2.5} concentrations that pose severe public health risks, yet forecasting rare, hazardous-level spikes remains

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Research

From Theory to Application: A Practical Introduction to Neural Operators in Scientific Computing

DGX agent

arXiv:2503.05598v3 Announce Type: replace-cross Abstract: This review examines neural operator architectures for learning solution operators of parametric partial differential equations (PDEs), with a

researcharxiv-cs-lg

10 Jul 2026

FSD-VLN: Fast-Slow Dual-System Modeling for Aerial Long-Horizon Vision-Language Navigation

arXiv:2607.08359v1 Announce Type: cross Abstract: Vision-Language Navigation (VLN) enables UAV autonomous navigation in unknown environments by mapping language instructions to real-time visual inputs

Infinity-Parser2 Technical Report

arXiv:2607.07836v1 Announce Type: new Abstract: We present Infinity-Parser2, a large multimodal model that couples a controllable data-synthesis pipeline with multi-task reinforcement learning for end

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE

arXiv:2607.07740v1 Announce Type: cross Abstract: Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workfl

Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs

arXiv:2607.07903v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable capabilities but remain highly vulnerable to adversarial prompts and jailbreak attacks. Existing appro

safetyarxiv-cs-ai

Applications

MobiDiff: Semantic-Aware Multi-Channel Discrete Diffusion for Human Mobility Data Generation

arXiv:2607.08357v1 Announce Type: new Abstract: Human mobility data are essential for transportation optimization, urban planning, and resource allocation, yet real-world mobility data are costly to c

applicationsarxiv-cs-ai

Modular Pretraining Enables Access Control

arXiv:2607.08077v1 Announce Type: new Abstract: AI developers face a dual-use dilemma. An AI capability that helps one user cure a disease can help another synthesize one. This dilemma could be resolv

researcharxiv-cs-lg

Applications

Monocular Vision Based Control Framework for Grasping

arXiv:2607.07897v1 Announce Type: new Abstract: Grasping in unstructured environments requires handling objects with widely different mechanical properties, from soft and deformable items to rigid eve

applicationsarxiv-cs-ro

Multi-Modal, Multi-Environment Machine Teaching for Robust Reward Learning

arXiv:2607.08647v1 Announce Type: cross Abstract: As autonomous agents are increasingly deployed across diverse operational contexts, aligning their behavior with human intent demands reward functions

OmniOPSD: Rationale-Privileged On-Policy Self-Distillation for Affective Computing

arXiv:2606.15920v2 Announce Type: replace Abstract: Reinforcement learning for multimodal large language models (MLLMs) is often hindered by severe reward sparsity in complex reasoning tasks. This cha

local-aiarxiv-cs-cv

On Exploring Input Resolution Scaling For Anytime LiDAR Object Detection

arXiv:2607.08391v1 Announce Type: cross Abstract: Making tradeoffs between execution latency and result utility (i.e., anytime computing) for adapting to dynamic operational requirements has been show

agentsarxiv-cs-lg

Open-Vocabulary Object-Goal Navigation by Generalizing Semantic Mapping with Dense CLIP

arXiv:2407.09016v2 Announce Type: replace Abstract: Object-oriented embodied navigation tasks require agents to locate specific objects, either defined by category or images, in unseen environments. W

researcharxiv-cs-ro

Playing ZendoWorld: Challenging AI Agents on Active Visual Concept Induction

arXiv:2607.08233v1 Announce Type: new Abstract: A central challenge in building intelligent systems is enabling agents to jointly perceive complex inputs, form hypotheses about hidden patterns, and de

RhyMix: A Lightweight Adaptive Multi-Rhythm Network for Long-Term Time Series Forecasting

arXiv:2607.08234v1 Announce Type: cross Abstract: Real-world time series exhibit complex dynamics characterized by multiple simultaneous temporal patterns: short-term fluctuations, periodic seasonal c

local-aiarxiv-cs-ai

SQuaD-SQL: Efficient Text-to-SQL with Small Language Models via LLM-Guided Knowledge Distillation

model-releasesarxiv-cs-cl

arXiv:2607.08161v1 Announce Type: new Abstract: Text-to-SQL is a fundamental task in natural language processing that enables users to interact with structured databases using natural language. While

Applications

StreamVLN: Streaming Vision-and-Language Navigation via SlowFast Context Modeling

arXiv:2507.05240v2 Announce Type: replace-cross Abstract: Vision-and-Language Navigation (VLN) in real-world settings requires agents to process continuous visual streams and generate actions with low

applicationsarxiv-cs-cv

Structured Pruning of Large Language Models via Power Transformation and Sign-Preserving Score Aggregation with Adaptive Feature Retention

arXiv:2607.08027v1 Announce Type: cross Abstract: This paper proposes an improved structured pruning method for large language models (LLMs) that addresses key challenges in adapting Adaptive Feature

Texture Representations in Deep Vision Models: Comparing CNNs, Vision Transformers, and Human Perception

arXiv:2607.08321v1 Announce Type: new Abstract: In computational vision science, Convolutional Neural Networks (CNNs) have emerged as a popular model of biological vision because of the alignment they

safetyarxiv-cs-cv

Time-to-Collision Based Dynamic Obstacle Avoidance Using Pretrained Vision Models for Robots in Unstructured Environments

arXiv:2607.07885v1 Announce Type: cross Abstract: Dynamic obstacle avoidance in unstructured outdoor environments remains a critical challenge for autonomous mobile robots, particularly when large-sca

Towards Efficient Large Language Model Serving: A Survey on System-Aware KV Cache Optimization

arXiv:2607.08057v1 Announce Type: cross Abstract: Despite the rapid advancements of large language models (LLMs), LLM serving systems remain memory-intensive and costly. The key-value (KV) cache, whic

TypeProbe: Recovering Type Representations from Hidden States of Pre-trained Code Models

arXiv:2607.08339v1 Announce Type: cross Abstract: State-of-the-art code models achieve impressive performance, yet the extent to which they internally encode type information remains poorly understood

UltraX: Refining Pre-Training Data at Scale with Adaptive Programmatic Editing

arXiv:2607.08646v1 Announce Type: cross Abstract: As available training data approaches its physical limit, gains from Scaling Laws have begun to diminish. Consequently, improving Large Language Model

safetyarxiv-cs-ai

Understanding and Mitigating the Video-Action Generalization Gap via Temporal Ratio

model-releasesarxiv-cs-cv

arXiv:2607.08127v1 Announce Type: new Abstract: Generative video foundation models exhibit strong compositional priors, yet world-action models (WAMs) and video-action models (VAMs) often lose these p

Validity of LLMs as data annotators: AMALIA on authority

arXiv:2607.08731v1 Announce Type: cross Abstract: A national language model offers a linguistic community its own instrument for measuring what its citizens say and value. Portugal's AMALIA, a publicl

VEGAS: Human-Aligned Video Caption Evaluation via Gaze

arXiv:2607.08489v1 Announce Type: cross Abstract: Vision-language models excel at video captioning, yet typically generate descriptions that fail to capture individual viewers' attention. We propose V

VocaDet: Sample-Driven Open-Vocabulary Object Detection and Segmentation via Visual Tokenization and Vector Database Retrieval

arXiv:2607.08541v1 Announce Type: cross Abstract: Open-vocabulary object detection and segmentation aim to recognize arbitrary objects beyond predefined categories. Although recent vision-language and

WCog-VLA: A Dual-Level World-Cognitive Vision-Language-Action Model for End-to-End Autonomous Driving

arXiv:2607.08375v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving. However, existing methods either lack comprehensive world cognition o

WebSwarm: Recursive Multi-Agent Orchestration for Deep-and-Wide Web Search

arXiv:2607.08662v1 Announce Type: cross Abstract: Large language model (LLM)-based web search agents are transforming information seeking from simple factoid question answering into complex, deep-and-

local-aiarxiv-cs-ai

When Thinking Hurts: Epistemic Signals in the Reasoning Chains of Visual Language Models

arXiv:2607.08059v1 Announce Type: cross Abstract: Uncertainty quantification for visual language models (VLMs) conventionally targets the answer token distribution. We provide the first three-family e

Accurate, Interdisciplinary and Transparent Structure-property Understanding with Deep Native Structural Reasoning

arXiv:2607.07708v1 Announce Type: cross Abstract: Structure-property relationships are foundational to biology, chemistry and materials science, where function, reactivity and physical response emerge

Activation Quantization of Vision Encoders Needs Prefixing Registers

arXiv:2510.04547v5 Announce Type: replace-cross Abstract: Large pretrained vision encoders are central to multimodal intelligence, powering applications from on-device vision processing to vision-lang

local-aiarxiv-cs-cv

Agon: Competitive Cross-Model RL with Implicit Rival Grading of Reasoning

arXiv:2607.07690v1 Announce Type: cross Abstract: Reinforcement learning from verifiable rewards (e.g. GRPO) is the engine behind today's reasoning models, yet it grades only the final answer. On hard

Audio Sentiment Analysis via Distillation and Cross-Modal Integration of Generated Multilingual Transcripts

arXiv:2607.06611v1 Announce Type: cross Abstract: Automatically recognizing the sentiment, positive or negative, from speech is a challenging task, requiring both the analysis of vocal inflections and

Bi-PT: Bidirectional Cross-Attention Point Transformers for Four-Chamber Heart Reconstruction from Sparse Cardiac MRI Data

arXiv:2607.06923v1 Announce Type: new Abstract: We propose Bi-PT, a pipeline for reconstructing 3D four-chamber human heart meshes from clinical sparsely sampled cardiac magnetic resonance imaging (CM

researcharxiv-cs-cv

CaLiSym: Learning Symplectic Dynamics of Real-World Systems through Structured Canonical Lifts

model-releasesarxiv-cs-lg

arXiv:2607.06824v1 Announce Type: cross Abstract: Physics-informed learning promises data-efficient and stable dynamics prediction, yet its strongest geometric guarantees have largely remained confine

Tutorials

Can We Really Learn One Representation to Optimize All Rewards?

arXiv:2602.11399v2 Announce Type: replace-cross Abstract: As unsupervised pretraining becomes increasingly ubiquitous in reinforcement learning, a more thorough theoretical understanding of these meth

tutorialsarxiv-cs-ai

CoMind: Understanding Collaborative Human Activity from Multiple Minds and Views

arXiv:2607.06691v1 Announce Type: new Abstract: Human-human collaboration is a fundamental aspect of everyday life, essential to success in a wide range of goal-directed activities from household task

agentsarxiv-cs-cv

Context-Aware Force Estimation for Deformable Tool Manipulation in Robotic Environmental Swabbing via Few-Shot Continual Adaptation

model-releasesarxiv-cs-ro

arXiv:2607.07574v1 Announce Type: new Abstract: Robotic surface swabbing requires sustained interaction between a compliant tool and heterogeneous environments, where accurate estimation of tip-level

CRIS: Cross-Plane Self-Supervised Isotropic Restoration for Anisotropic Volumetric Imaging Across Modalities

arXiv:2606.15967v2 Announce Type: replace Abstract: Anisotropic volumetric acquisitions are common in clinical MRI and volume electron microscopy (vEM), where sparse through-plane sampling creates thi

researcharxiv-cs-cv

DASH: Dynamic Audio-Driven Semantic Chunking for Efficient Omnimodal Token Compression

arXiv:2603.15685v2 Announce Type: replace-cross Abstract: Omnimodal large language models (OmniLLMs) jointly process audio and visual streams, but the resulting long multimodal token sequences make in

safetyarxiv-cs-ai

DiPhon: Diffusion on Graphons for Scalable Graph Generation

arXiv:2607.07232v1 Announce Type: cross Abstract: Diffusion models represent a leading paradigm for graph generation, with notable impact in domains such as molecular design. Yet, scaling these models

Does Bielik Know What It Doesn't Know? Activation Dispersion Separates Entity Familiarity from Factual Reliability Across Model Scale

arXiv:2607.07670v1 Announce Type: new Abstract: Large language models hallucinate most about entities they have never seen. We ask whether a model's activations betray entity familiarity before a sing

researcharxiv-cs-cl

Hardware

DYNA-PRUNER: Input-Adaptive Data-Model Co-Pruning for Efficient and Scalable Spatio-Temporal Media Prediction

arXiv:2606.15346v2 Announce Type: replace Abstract: Spatio-temporal prediction supports radar/satellite nowcasting and city-scale traffic monitoring, but modern models are often too expensive for real

hardwarearxiv-cs-cv

ECHO: Ego-Centric modeling of Human-Object interactions

arXiv:2508.21556v3 Announce Type: replace Abstract: Modeling human-object interactions (HOI) from an egocentric perspective is a critical yet challenging task, particularly when relying on sparse sign

researcharxiv-cs-cv

Ego-Human Motion Prediction with 3D-Aware LLM

model-releasesarxiv-cs-cv

arXiv:2607.07001v1 Announce Type: new Abstract: Anticipating human motion from an egocentric perspective is fundamental for proactive assistance in AR/VR, human-robot collaboration, and embodied AI. W

Explain Before You Answer: A Survey on Compositional Visual Reasoning

arXiv:2508.17298v3 Announce Type: replace-cross Abstract: Compositional visual reasoning has emerged as a key research frontier in multimodal AI, aiming to endow machines with the human-like ability t

Format-Controlled Multi-Scale JPEG Compression Response Analysis for Image-Level Forgery Screening

arXiv:2607.06615v1 Announce Type: cross Abstract: Image forgery detection is a critical task in digital forensics, yet many deep-learning localization approaches are typically GPU-accelerated and comp

local-aiarxiv-cs-cv