Search: “inference”

EvoIR-Agent: Self-Evolving Image Restoration Agentic System via Experience-Driven Learning

arXiv:2605.22208v1 Announce Type: new Abstract: Multimodal Large Language Model (MLLM)-driven image restoration agent demonstrates effectiveness in degradation coupling scenarios by flexibly selecting

agentsarxiv-cs-cv

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Research

ForeSplat: Optimization-Aware Foresight for Feed-Forward 3D Gaussian Splatting

DGX agent

arXiv:2605.22020v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) models offer fast single-pass reconstruction,but scaling them to match per-scene optimization quality is funda

researcharxiv-cs-cv

22 May 2026

From Recognition to Reasoning: Benchmarking and Enhancing MLLMs on Real-World Receipt Document Understanding

arXiv:2605.22413v1 Announce Type: new Abstract: Extracting structured information from visual documents (Visual Information Extraction, VIE) is a cornerstone of business automation. While recent Multi

Higher Order Reasoning for Collaborative Communicationless Mobile Robot Operations

arXiv:2605.21901v1 Announce Type: new Abstract: In communicationless environments, multi-robot systems must operate without the constant information exchange that many coordination strategies typicall

researcharxiv-cs-ro

Hy-MT2: A Family of Fast, Efficient and Powerful Multilingual Translation Models in the Wild

model-releasesarxiv-cs-cl

arXiv:2605.22064v1 Announce Type: new Abstract: Hy-MT2 is a family of fast-thinking multilingual translation models designed for complex real-world scenarios. It includes three model sizes: 1.8B, 7B,

I built a free demo for Pixal3D (Tencent new image-to-3D model)

local-air-stablediffusion

Pixal3D is a Tencent image-to-3D model that generates high-fidelity 3D assets from a single image by explicitly lifting pixel features into 3D through back-projection to establish direct pixel-to-3D c

InfVSR: Breaking Length Limits of Generic Video Super-Resolution

arXiv:2510.00948v2 Announce Type: replace Abstract: Real-world videos often extend over thousands of frames. Existing generative video super-resolution (VSR) approaches, however, face two persistent c

Interpreting and Enhancing Emotional Circuits in Large Vision-Language Models via Cross-Modal Information Flow

arXiv:2605.21980v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) represent a significant leap towards empathetic agents, demonstrating remarkable capabilities in emotion understand

Introducing Qwen3.7-Max from @Alibaba_Qwen, Qwen’s flagship model for the agent era with 1M context and leading performance across agentic c…

model-releasestogether-ai--x

Introducing Qwen3.7-Max from @Alibaba_Qwen, Qwen’s flagship model for the agent era with 1M context and leading performance across agentic coding, reasoning, and long-horizon autonomy. AI natives can

LACO: Adaptive Latent Communication for Collaborative Driving

arXiv:2605.22504v1 Announce Type: cross Abstract: Collaborative driving aims to improve safety and efficiency by enabling connected vehicles to coordinate under partial observability. Recent approache

safetyarxiv-cs-cv

Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models

arXiv:2605.21573v1 Announce Type: new Abstract: We introduce Lens, a 3.8B-parameter T2I model that achieves performance competitive with, and in several cases surpassing, state-of-the-art models with

LIDSA: Cognitive Arbitration for Signal-Free Autonomous Intersection Management

arXiv:2605.12321v2 Announce Type: replace Abstract: Large language models (LLMs) show strong potential for Intelligent Transportation Systems (ITS), particularly in tasks requiring situational reasoni

agentsarxiv-cs-ai

Mapping Tomato Cropping Systems in California Using AlphaEarth Geospatial Embeddings and Deep Learning Analysis

arXiv:2605.21804v1 Announce Type: cross Abstract: Field-scale crop maps support supply-chain forecasting and policy, yet statewide crop identification still often depends on retrospective surveys or r

safetyarxiv-cs-cv

MLLMs Know When Before Speaking: Revealing and Recovering Temporal Grounding via Attention Cues

arXiv:2605.21954v1 Announce Type: new Abstract: Video temporal grounding (VTG), which localizes the start and end times of a queried event in an untrimmed video, is a key test of whether multimodal la

MotionDPS: Motion-Compensated 3D Brain MRI Reconstruction

arXiv:2605.22121v1 Announce Type: new Abstract: Magnetic resonance imaging (MRI) is highly susceptible to patient motion due to its relatively long acquisition times and the fact that data are acquire

NuExtract3 released: open-weight 4B VLM for Markdown, OCR and structured extraction (self-hostable) [P]

model-releasesr-machinelearning

NuExtract3 is a unified 4B vision-language reasoning model for document understanding that combines structured information extraction with image-to-Markdown conversion, suitable for OCR and RAG prepro

Probabilistic Attribution For Large Language Models

arXiv:2605.21726v1 Announce Type: new Abstract: The generative nature of Large Language Models (LLMs) is reflected in the conditional probabilities they compute to sample each response token given the

researcharxiv-cs-cl

Applications

Quantizing Whisper-small: How design choices affect ASR performance

arXiv:2511.08093v2 Announce Type: replace-cross Abstract: Large speech recognition models like Whisper-small achieve high accuracy but are difficult to deploy on edge devices due to their high computa

applicationsarxiv-cs-cl

Reflective Prompt Tuning through Language Model Function-Calling

model-releasesarxiv-cs-cl

arXiv:2605.21781v1 Announce Type: new Abstract: Large language models (LLMs) have become increasingly capable of following instructions and complex reasoning, making prompting a flexible interface for

Reinforcing VLAs in Task-Agnostic World Models

arXiv:2605.12334v2 Announce Type: replace Abstract: Post-training Vision-Language-Action (VLA) models via reinforcement learning (RL) in learned world models has emerged as an effective strategy to ad

safetyarxiv-cs-ai

SceneGraphGrounder: Zero-Shot 3D Visual Grounding via Structured Scene Graph Matching

arXiv:2605.21788v1 Announce Type: new Abstract: Zero-shot 3D visual grounding requires localizing objects in unstructured environments from free-form natural language. Recent vision-language model (VL

Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning

arXiv:2605.22511v1 Announce Type: cross Abstract: Post-training has become the dominant recipe for turning a language model into a competent search-augmented reasoning agent. A line of recent work pus

SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers

arXiv:2605.22668v1 Announce Type: new Abstract: Diffusion transformers (DiTs) have emerged as a dominant architecture for text-to-image generation, yet their performance drops when generating at resol

Tutorials

TextTeacher: What Can Language Teach About Images?

arXiv:2605.22098v1 Announce Type: new Abstract: The platonic representation hypothesis suggests that sufficiently large models converge to a shared representation geometry, even across modalities. Mot

tutorialsarxiv-cs-cv

Translating Signals to Languages for sEMG-Based Activity Recognition

arXiv:2605.22403v1 Announce Type: new Abstract: Surface electromyography (sEMG) signal-based activity recognition has attracted increasing research attention in recent years. To develop accurate sEMG

using ltx 2.3 i2v 3d animation with reference voice using TalkVid Lora.

local-air-stablediffusion

ID-LoRA (Identity-Driven In-Context LoRA) enables identity-preserving audio-video generation by simultaneously dictating the scene's visual content, environmental acoustics, and speaking style while p

VEELA: A Clinically-Constrained Benchmark for Liver Vessel Segmentation in Computed Tomography Angiography

arXiv:2605.22357v1 Announce Type: new Abstract: Accurate segmentation of hepatic and portal vessels in contrast-enhanced computed tomography angiography (CTA) remains challenging due to complex vascul

Hardware

WorldKV: Efficient World Memory with World Retrieval and Compression

arXiv:2605.22718v1 Announce Type: new Abstract: Autoregressive video diffusion models have enabled real-time, action-conditioned world generation. However, sustaining a persistent world, where revisit

hardwarearxiv-cs-cv

A Human-in-the-Loop Framework for Efficient Prompt Selection in Microscopy Vision-Language Models

arXiv:2605.20495v1 Announce Type: new Abstract: Deep-learning pipelines for microscopy image classification often require expensive, labor- and time-intensive expert annotation to produce high-quality

A Mechanistic Study of Tabular Foundation Models

arXiv:2605.21288v1 Announce Type: new Abstract: Tabular foundation models with different architectures converge in accuracy across a range of classification and regression tasks. This raises questions

researcharxiv-cs-lg

AFD-INSTRUCTION: A Comprehensive Antibody Instruction Dataset with Functional Annotations for LLM-Based Understanding and Design

arXiv:2602.04916v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have significantly advanced protein representation learning. However, their capacity to interpret and design anti

Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control

model-releasesarxiv-cs-lg

arXiv:2512.23292v3 Announce Type: replace-cross Abstract: The prevailing paradigm in AI for physical systems (scaling general-purpose foundation models toward universal multimodal reasoning) confronts

AI Studio unlocks full-stack vibe coding with Cloud Run, Firebase, and Cloud SQL, no credit card required

At Google I/O 2026, we announced updates to the integration between Google AI Studio and Google Cloud: New users can deploy up to two full-stack applications to the Google Cloud Starter Tier, no billi

agentsgoogle-cloud-ai

APM: Evaluating Style Personalization in LLMs with Arbitrary Preference Mappings

model-releasesarxiv-cs-cl

arXiv:2605.21063v1 Announce Type: new Abstract: Typical LLM responses tend to follow a default style, even though users often have distinct preferences regarding tone, verbosity, and formality that th

Tutorials

Automatic Discovery of Disease Subgroups by Contrasting with Healthy Controls

arXiv:2605.21301v1 Announce Type: cross Abstract: In biomedical Subgroup Discovery, practitioners are interested in discovering interpretable and homogeneous subgroups within a group of patients. In t

tutorialsarxiv-cs-cv

AVSD: Adaptive-View Self-Distillation by Balancing Consensus and Teacher-Specific Privileged Signals

arXiv:2605.20643v1 Announce Type: cross Abstract: Self-distillation enables language models to learn on-policy from their own trajectories by using the same model as both student and teacher, with the

b9255

Release b9255 of llama.cpp features a Hexagon HMX quantized matmul rework (#23368), including updates to debug logging, dequantization logic using HVX vectors, removal of non-pipelined quantization op

b9259

Release b9259 of llama.cpp fixes a nullptr crash in the speculative common module's get_devices_str function (PR #23386). The fix addresses an issue where ggml_backend_dev_by_name appends a nullptr se

b9260

Release b9260 of llama.cpp includes OpenCL backend refactoring that improves initialization, GPU identification, and performance by caching global memory size in device context. llama.cpp enables LLM

b9264

b9264 is a llama.cpp release that includes improvements to HunyuanVL model support, merging HunyuanOCR functionality and fixing vision precision issues. This build represents an intermediate developme

Bayesian Preference Learning for Test-Time Steerable Reward Models

arXiv:2602.08819v2 Announce Type: replace-cross Abstract: Reward models are central to aligning language models with human preferences via reinforcement learning (RL). As RL is increasingly applied to

Block-Sparse Global Attention for Efficient Multi-View Geometry Transformers

arXiv:2509.07120v2 Announce Type: replace Abstract: Efficient and accurate feed-forward multi-view reconstruction has long been an important task in computer vision. Recent transformer-based models li

Causal Unlearning in Collaborative Optimization: Exact and Approximate Influence Reversal under Adversarial Contributions

model-releasesarxiv-cs-lg

arXiv:2605.20341v1 Announce Type: new Abstract: Federated learning systems must support data deletion requests to comply with privacy regulations, yet retraining from scratch after each deletion is co

ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning

arXiv:2605.20385v1 Announce Type: new Abstract: Recent progress in promptable segmentation has shifted visual perception from object-level localization toward concept-level understanding. However, the

Applications

CT-OT Flow: Estimating Continuous-Time Dynamics from Discrete Temporal Snapshots

arXiv:2505.17354v3 Announce Type: replace Abstract: In many real-world settings--e.g., single-cell RNA sequencing, mobility sensing, and environmental monitoring--data are observed only as temporally

applicationsarxiv-cs-lg

Demo-JEPA: Joint-Embedding Predictive Architecture for One-shot Cross-Embodiment Imitation

arXiv:2605.20811v1 Announce Type: new Abstract: Robotic imitation learning is often treated as reproducing demonstrated actions, but actions are inherently embodiment-specific. When demonstrations com

agentsarxiv-cs-ro

Distill to Think, Foresee to Act: Cognitive-Physical Reinforcement Learning for Autonomous Driving

arXiv:2605.21139v1 Announce Type: new Abstract: Current end-to-end autonomous driving models are fundamentally constrained by the behavioral cloning ceiling of imitation learning. While reinforcement

safetyarxiv-cs-cv

Do Vision--Language Models Understand 3D Scenes or Just Catalogue Objects?

arXiv:2605.20448v1 Announce Type: new Abstract: Vision--language models reliably name objects in a scene, but do they represent the 3D layout those objects inhabit? We introduce a 3,034-sample human-c