Search: “inference”

VaseMuseum: Digital Intelligent Museum for Ancient Greek Pottery

arXiv:2607.06374v1 Announce Type: new Abstract: Vision-language models (VLMs) have made interactive digital museums increasingly feasible by connecting 3D digitization with natural-language artifact e

agentsarxiv-cs-cv

8 Jul 2026

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We raised 130M @ 1B for our series A To build the open superintelligence stack for everyone Pre-training concentrated frontier AI in a han…

DGX agent

We raised 130M @ 1B for our series A To build the open superintelligence stack for everyone Pre-training concentrated frontier AI in a handful of labs. RL changes who can build frontier AI and just wo

hardwareswyx--x

8 Jul 2026

x-Prediction Is All You Need:Training-Free Accelerated Generation via Endpoint Decodability

arXiv:2607.06114v1 Announce Type: cross Abstract: Diffusion and flow matching models generate high-quality samples, but their ODE samplers often need tens to hundreds of neural function evaluations (N

8 Jul 2026

3DMPE: 3D Multi-Perspective Embedding

arXiv:2607.04898v1 Announce Type: new Abstract: We study 3D point cloud reconstruction from multiple partially observed 2D projections. Given two or more projections of an unknown 3D point cloud, toge

A Few Teacher Steps Go a Long Way: Cost-Efficient On-Policy Data Augmentation for Agent Post-Training

arXiv:2607.04574v1 Announce Type: cross Abstract: For LLM agents, supervised fine-tuning is not only about teacher labels' quality, but also about which interaction contexts those labels condition on.

Local Ai

A Multimodal Reasoning Typology for Grounding Chart-Image Coherence in Science Communication

arXiv:2607.05222v1 Announce Type: new Abstract: Charts and images appear together throughout scientific publications, yet most computational work does not characterize their coherence. We argue that a

local-aiarxiv-cs-cv

A Preliminary Study on Explaining Risk of Code Changes using LLM-Based Prediction Models

arXiv:2607.02782v1 Announce Type: cross Abstract: Predictions by machine learning (ML) and artificial intelligence (AI) models are often received skeptically unless they are paired with intelligible e

Adaptive Margin RLHF via Preference over Preferences

arXiv:2509.22851v4 Announce Type: replace-cross Abstract: Margin-based optimization is fundamental to improving generalization and robustness in classification tasks. In the context of reward model le

AdaptiveSplat:Texture Aware Controllable 3D Gaussian Allocation for Feed-Forward Reconstruction

arXiv:2607.04256v1 Announce Type: new Abstract: Current feed-forward 3D reconstruction methods predict pixel aligned Gaussian primitives, resulting in highly redundant representations. A natural solut

Agentic SABRE: An Uncertainty-Aware Neuro-Symbolic Multi-Agent Framework for Adaptive Ransomware Detection

arXiv:2607.04292v1 Announce Type: new Abstract: Ransomware has evolved into a complex, adaptive, and fast-moving adversary category in which static signatures and monolithic classifiers fail to genera

AGL-1: The Enterprise AI Governance Layer as a Control Plane for Trusted Enterprise Intelligence

arXiv:2607.03516v1 Announce Type: cross Abstract: Enterprise artificial intelligence is moving from isolated experimentation toward operational dependency across copilots, retrieval-augmented generati

AIFS-SUBS: Extending Data-Driven Forecasting to Sub-Seasonal Timescales

arXiv:2607.05100v1 Announce Type: cross Abstract: Data-driven models now rival numerical weather prediction in the medium range, but extending them to sub-seasonal lead times raises challenges absent

Alignment-Guided Largest Table Overlap Size Estimation

arXiv:2607.03049v1 Announce Type: new Abstract: Fast estimation of the size of the largest overlap between tables enables blocking and query-by-table retrieval in large table repositories. The first a

safetyarxiv-cs-cl

An Exploration of Agentic Information Fusion for Test Maintenance Prediction

arXiv:2607.04786v1 Announce Type: cross Abstract: Test maintenance is a critical, yet costly, activity - particularly as codebases rapidly evolve. To assist, we present MAST, a multi-agent framework t

AnyStyle: A Single LoRA is Sufficient for Image-Guided Style Transfer

arXiv:2607.04677v1 Announce Type: new Abstract: Image-guided style transfer aims to apply the artistic characteristics of a style image to a content image while preserving its semantic structure and l

AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generation

model-releasesarxiv-cs-cv

arXiv:2606.12555v2 Announce Type: replace-cross Abstract: Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a

Local Ai

AULLM++: Structured-Token-Conditioned Large Language Models for Micro-Expression Action Unit Detection

arXiv:2603.08387v2 Announce Type: replace Abstract: Micro-expression Action Unit (AU) detection identifies localized AUs from subtle facial muscle activations, providing a foundation for decoding affe

local-aiarxiv-cs-cv

Aura: Consistent Multi-Subject Video Generation via VLM-Grounded Semantic Alignment

arXiv:2607.04311v1 Announce Type: new Abstract: Subject-driven and multi-element video generation are central to controllable video synthesis, but existing methods still struggle to preserve identity

Awakening Diffusion Transformers: Eliciting Stronger Generation and Understanding via Massive Activation Modulation

arXiv:2607.02968v1 Announce Type: new Abstract: Massive Activations (MAs) have been widely observed in Transformer-based models, yet their structure and functional roles in Diffusion Transformers (DiT

Local Ai

b9894

local-aillama-cpp-releases

Release b9894 of llama.cpp was published on July 7, 2026 , and includes a Vulkan backend fix to check src0 type in GGML_OP_SET_ROWS to avoid failures due to unimplemented f16 support . Llama.cpp is th

BanglaMemeEvidence: A Multimodal Benchmark Dataset for Explanatory Evidence Detection in Bengali Memes

arXiv:2607.03981v1 Announce Type: cross Abstract: Memes have become influential communication tools on social media, combining viral visuals with concise messaging to convey impactful ideas. While sub

Bayesian Invariance Modeling of Multi-Environment Data

arXiv:2506.22675v4 Announce Type: replace-cross Abstract: Invariant prediction [Peters et al., 2016] analyzes feature/outcome data from multiple environments to identify invariant features - those wit

researcharxiv-cs-lg

Beyond Independent Labels: Schwartz-Geometry Decoding for Human Value Detection

arXiv:2607.05052v1 Announce Type: cross Abstract: Human value detection is commonly formulated as sentence-level multi-label classification over the 19 refined Schwartz values, typically predicted as

Beyond Isolated Objects: Relationship-aware Open Vocabulary Scene Understanding via 3D Scene Graph Analysis

arXiv:2607.05348v1 Announce Type: new Abstract: Open-vocabulary 3D scene understanding aims to segment 3D scenes beyond predefined categories by transferring semantic knowledge from vision-language mo

Beyond Scene Priors: Fine-Grained Traffic Scene Reasoning with Benchmarking and Query-Guided Small-Object Focus

model-releasesarxiv-cs-cv

arXiv:2607.04149v1 Announce Type: new Abstract: In safety-critical traffic scenarios, answering complex questions relies on minute, localized visual cues. However, standard Multimodal Large Language M

BoRP: Bootstrapped Regression Probing for Scalable and Human-Aligned LLM Evaluation

arXiv:2601.18253v2 Announce Type: replace-cross Abstract: Accurate evaluation of user satisfaction is critical for iterative development of conversational AI. However, for open-ended assistants, tradi

BrainNormalizer: Anatomy-Informed Pseudo-Healthy Brain Reconstruction from Tumor MRI via Edge-Guided ControlNet

arXiv:2511.12853v2 Announce Type: replace-cross Abstract: Brain tumors induce complex structural deformations that obscure the patient' s original neuroanatomy, making it difficult to distinguish tumo

CDST: Color Disentangled Style Transfer for Universal Style Reference Customization

arXiv:2506.13770v2 Announce Type: replace Abstract: We introduce Color Disentangled Style Transfer (CDST), a novel and efficient two-stream style transfer training paradigm which completely isolates c

City landscape in sight: A crowdsourced framework for unlocking urban-scale window view perceptions from real estate imagery

arXiv:2606.15198v2 Announce Type: replace Abstract: City landscapes viewed through home windows influence quality of life, yet perceptions of actual window views at the urban scale remain understudied

CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving

arXiv:2607.02841v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E-AD) aims to directly map raw sensor information to driving actions. Recently, with the rapid advancement of multi-m

CoACT: Action-Preserving Observation Compression for Coding Agents

arXiv:2607.02911v1 Announce Type: cross Abstract: LLM-based coding agents solve software-engineering tasks through iterative interactions with development environments, where returned observations acc

CogRad: A Cognitively-Inspired Multi-Agent Framework for Radiology Report Generation

arXiv:2607.03853v1 Announce Type: new Abstract: Automated radiology report generation (RRG) can ease radiologist workload, yet most existing systems produce a report in a single forward pass, with no

agentsarxiv-cs-cv

Tutorials

CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion

arXiv:2607.05046v1 Announce Type: new Abstract: Evaluating generative AI models is a routine, but resource-intensive, process that is conducted over and over again during the course of model developme

tutorialsarxiv-cs-lg

Cortex: A Bidirectionally Aligned Embodied Agent Framework for Long-horizon Manipulation

arXiv:2607.05377v1 Announce Type: cross Abstract: While recent Vision-Language-Action (VLA) models show promise toward generalist manipulation policies, they struggle with long-horizon tasks due to th

Coverage-Controlled Preference Mining from Noisy Claim Verification for Evidence-Grounded Generation

arXiv:2603.10494v2 Announce Type: replace Abstract: Evidence-grounded generation produces summaries whose claims should be supported by supplied evidence, but claim-level verifiers provide noisy feedb

safetyarxiv-cs-cl

Criterion-Conditional In-Context Learning: Evaluating Criterion-Shift Adaptation in Vision-Language Models

arXiv:2607.02575v1 Announce Type: cross Abstract: Vision-language models can perform new tasks without parameter updates through in-context learning (ICL), whose core mechanism is utilizing the suppor

CritiqueDriveVLM: From Verifier-Guided Reinforcement Learning to Latent Thought Distillation for Autonomous Driving

arXiv:2607.04179v1 Announce Type: cross Abstract: End-to-end Vision-Language Models (VLMs) show immense potential in autonomous driving. However, standard Supervised Fine-Tuning (SFT) often suffers fr

DeGenseGS: Geometrically and Semantically Decoupled Surgical Scene Understanding in 4D Gaussian Splatting

arXiv:2607.04761v1 Announce Type: new Abstract: Real-time, text-promptable 4D reconstruction is indispensable for autonomous surgical interaction. Severe misalignment between semantic meaning and phys

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)

arXiv:2607.04223v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) reduces but does not eliminate hallucination, and existing detectors return a single answer-level score that does

DiCE-CIR: Direct Composition Learning for Efficient Zero-Shot Composed Image Retrieval

arXiv:2607.04665v1 Announce Type: new Abstract: Zero-shot composed image retrieval (ZS-CIR) aims to retrieve a target image from a multimodal query consisting of a reference image and an edit text des

DistillH-Mamba: A Hypergraph-Mamba-Based Knowledge Distillation Model for Efficient Impact Fall Detection

arXiv:2607.03156v1 Announce Type: new Abstract: Falls among the elderly represent a significant public health concern due to their prevalence, consequences, and societal burden. While deep learning ha

Do All Visual Tokens Matter Equally? Object-Evidence Preserving Token Merging for Vision-Language Retrieval

arXiv:2607.04605v1 Announce Type: cross Abstract: Multi-vector vision-language retrieval preserves fine-grained visual evidence through maximum-similarity late interaction, but dense image-side tokens

Don't Commit Alone: Joint Token Commitment in Diffusion Large Language Models

arXiv:2607.04469v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) commit multiple tokens per denoising step by decoding each selected position independently from the shared conte

researcharxiv-cs-cl

dOPSD: On-Policy Self-Distillation for Diffusion Language Models

arXiv:2607.04428v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by iteratively denoising a masked sequence, offering a parallel alternative to autoregressive mo

DSWAM: A Dual-System World Action Foundation Model for Fine-Grained Robot Manipulation

arXiv:2607.04927v1 Announce Type: cross Abstract: World Action Models (WAMs) provide a promising alternative to Vision-Language-Action (VLA) policies by using video-based world modeling as dense super

Efficient bias mitigation in T2I diffusion models using Concept Graphs

arXiv:2607.03397v1 Announce Type: new Abstract: Text-to-Image diffusion models often propagate harmful bias inherited from the training data. Existing bias mitigation techniques typically intervene on

Efficient Flow Matching for Sparse-View CT Reconstruction

arXiv:2603.00205v2 Announce Type: replace-cross Abstract: Generative models, particularly Diffusion Models (DM), have shown strong potential for Computed Tomography (CT) reconstruction serving as expr

EVAS: Efficient Multimodal Temporal Forgery Localization via Audio-Visual Synergy and Steered Boundary Calibration

model-releasesarxiv-cs-cv

arXiv:2607.04472v1 Announce Type: new Abstract: The rapid proliferation of artificial intelligence-generated content necessitates reliable multimodal forensics. Beyond video-level binary classificatio