All entries

Slimmable ConvNeXt: Width-Adaptive Inference for Efficient Multi-Device Deployment

arXiv:2605.22677v1 Announce Type: new Abstract: Deploying vision models across devices with varying resource constraints, or even on a single device where available compute fluctuates due to battery s

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

SO-Mamba: State-Ownership Mamba for Unrolled MRI Reconstruction

DGX agent

arXiv:2605.22031v1 Announce Type: new Abstract: Accelerated MRI reconstruction requires recovering missing details while preserving anatomically coherent structures across large spatial regions. State

researcharxiv-cs-cv

22 May 2026

SONIC: Supersizing Motion Tracking for Natural Humanoid Whole-Body Control

arXiv:2511.07820v3 Announce Type: replace-cross Abstract: Despite the rise of billion-parameter foundation models trained across thousands of GPUs, similar scaling gains have not been shown for humano

SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation

arXiv:2605.22536v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have made rapid progress in spatial intelligence, yet existing spatial reasoning benchmarks largely assume pr

SpaceDrive: Infusing Spatial Awareness into VLM-based Autonomous Driving

arXiv:2512.10719v2 Announce Type: replace Abstract: End-to-end autonomous driving methods built on vision language models (VLMs) have undergone rapid development driven by their universal visual under

Spatial Memory for Out-of-Vision Manipulation in Vision-Language-Action

model-releasesarxiv-cs-ro

arXiv:2605.22283v1 Announce Type: new Abstract: We introduce SOMA, the Spatial Memory framework for Out-of-Vision Manipulation in Vision-Language-Action (VLA) models. Most existing VLAs implicitly ass

SpecHop: Continuous Speculation for Accelerating Multi-Hop Retrieval Agents

arXiv:2605.21965v1 Announce Type: new Abstract: Large language models increasingly use external tools such as web search and document retrieval to solve information-intensive tasks. However, multi-hop

agentsarxiv-cs-cl

Applications

Spectral Tail Auxiliary Learning for AI-Generated Image Detection

arXiv:2605.22751v1 Announce Type: new Abstract: As generative image models evolve rapidly, the perceptual gap between generated and real images continues to narrow, making AI-generated image detection

applicationsarxiv-cs-cv

SPIRAL: Self-Evolving Action-Conditioned Video Generation via Reflective Planning Agents

arXiv:2603.08403v3 Announce Type: replace Abstract: Long-horizon action-conditioned video generation aims to synthesize temporally coherent videos that follow complex action instructions over extended

ST-SimDiff: Balancing Spatiotemporal Similarity and Difference for Efficient Video Understanding with MLLMs

arXiv:2605.22158v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) face significant computational overhead when processing long videos due to the massive number of visual token

stable-worldmodel: A Platform for Reproducible World Modeling Research and Evaluation

arXiv:2605.21800v1 Announce Type: cross Abstract: World models are central to building agents that can reason, plan, and generalize beyond their training data. However, research on world models is cur

researcharxiv-cs-ro

Stdlib or Third-Party? Empirical Performance and Correctness of LLM-Assisted Zero-Dependency Python Libraries

arXiv:2605.21405v1 Announce Type: cross Abstract: Third-party Python libraries introduce dependency management overhead, supply chain risk, and deployment friction in constrained environments. A natur

agentsarxiv-cs-ai

Steins;Gate Drive: Semantic Safety Arbitration over Structured Futures for Latency-Decoupled LLM Planning

model-releasesarxiv-cs-ro

arXiv:2605.22456v1 Announce Type: new Abstract: Cloud-hosted LLM driver agents provide useful semantic judgments, but their inference latency exceeds stepwise vehicle-control windows. Learned world mo

STRUCTSENSE: A Task-Agnostic Agentic Framework for Structured Information Extraction with Human-In-The-Loop Evaluation and Benchmarking

arXiv:2507.03674v3 Announce Type: replace Abstract: Extracting structured information from scientific literature is critical for accelerating discovery, yet Large Language Models (LLMs) often struggle

agentsarxiv-cs-cl

Structural Anchor Pruning: Training-Free Multi-Vector Compression for Visual Document Retrieval

arXiv:2601.20107v2 Announce Type: replace-cross Abstract: Recent Vision-Language Models (e.g., ColPali) enable fine-grained Visual Document Retrieval (VDR) but incur prohibitive multi-vector index sto

Structure Retention in Embedding Spaces as a Predictor of Benchmark Performance

arXiv:2605.22202v1 Announce Type: new Abstract: In this paper, we show that high-performing embedding models organize their embedding spaces in a consistent way. We evaluate 25 contemporary embedding

Local Ai

Structured-Sparse Attention for Entity Tracking with Subquadratic Sequence Complexity

arXiv:2605.22476v1 Announce Type: cross Abstract: Entity tracking requires maintaining and updating latent states for entities and attributes over long sequences. Recent task-specific attention operat

local-aiarxiv-cs-cl

Sub-exponential Growth Dynamics in Complex Systems: A Piecewise Power-Law Model for the Diffusion of New Words and Names

arXiv:2511.04106v5 Announce Type: replace-cross Abstract: The diffusion of ideas and language in society has conventionally been described by S-shaped models, such as the logistic curve. However, the

Superhuman Safe and Agile Racing through Multi-Agent Reinforcement Learning

arXiv:2605.22748v1 Announce Type: new Abstract: Autonomous systems have achieved superhuman performance in isolation or simulation, yet they remain brittle in shared, dynamic real-world spaces. This f

safetyarxiv-cs-ro

Supervised Classification Heads as Semantic Prototypes: Unlocking Vision-Language Alignment via Weight Recycling

arXiv:2605.22484v1 Announce Type: new Abstract: Vision-Language Models (VLMs) excel at tasks like zero-shot classification and cross-modal retrieval by mapping images and text to a shared space, but t

safetyarxiv-cs-cv

SURGE: An Event-Centric Social Media Sentiment Time Series Benchmark with Interaction Structure

model-releasesarxiv-cs-ai

arXiv:2605.21198v1 Announce Type: cross Abstract: Public events on social media generate large volumes of discussion whose collective dynamics carry direct value for opinion forecasting and crisis res

Survive or Collapse: The Asymmetric Roles of Data Gating and Reward Grounding in Self-Play RL

arXiv:2605.22217v1 Announce Type: cross Abstract: Self-play reinforcement learning trains language models on their own generated tasks, co-evolving a proposer and solver without human labels. Recent s

Swift Sampling: Selecting Temporal Surprises via Taylor Series

arXiv:2605.22678v1 Announce Type: new Abstract: While most frames in long-form video are redundant, the critical information resides in temporal surprises: moments where the actual visual features dev

Applications

Symmetries Here and There, Combined Everywhere: Cross-space Symmetry Compositions in Robotics

arXiv:2605.22639v1 Announce Type: new Abstract: Robots exhibit a rich variety of symmetries arising from their mechanical structure and the properties of their tasks. Although many robotics problems e

applicationsarxiv-cs-ro

SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations

arXiv:2605.22564v1 Announce Type: new Abstract: Today, tool-calling agents are commonly evaluated or tested on static datasets of execution traces, including input commands, agent responses, and assoc

agentsarxiv-cs-cl

Applications

Synthetic Data Alone is Enough? Rethinking Data Scarcity in Pediatric Rare Disease Recognition

arXiv:2605.22767v1 Announce Type: new Abstract: Children with rare genetic diseases often exhibit distinctive facial phenotypes, yet developing computer vision systems for early diagnosis remains chal

applicationsarxiv-cs-cv

Tackle CSM in JPEG Steganalysis with Data Adaptation

arXiv:2605.21523v1 Announce Type: cross Abstract: Steganalysis models excel on benchmark datasets but struggle in the wild when analyzed images are produced by a processing pipeline unseen during trai

TacO: Benchmarking Tactile Sensors for Object Manipulation

arXiv:2605.21976v1 Announce Type: new Abstract: Vision-based learning from demonstrations has achieved remarkable success in enabling robots to perform manipulation tasks and high-level semantic reaso

safetyarxiv-cs-ro

Targeting Clause Type Distributions: a Picklock for Random Satisfiability Problems

model-releasesarxiv-cs-ai

arXiv:2605.20328v1 Announce Type: cross Abstract: Optimization problems such as the NP-complete 3-SAT provide an important benchmark for the difficult task of finding ground-states in strongly correla

Teaching AI Through Benchmark Construction: QuestBench as a Course-Based Practice for Accountable Knowledge Work

model-releasesarxiv-cs-ai

arXiv:2605.21413v2 Announce Type: new Abstract: As AI becomes part of everyday learning, many courses teach students to use it mainly as a productivity tool: how to prompt, search, summarize, write, c

Teaching Language Models to Forecast Research Success Through Comparative Idea Evaluation

arXiv:2605.21491v1 Announce Type: cross Abstract: As language models accelerate scientific research by automating hypothesis generation and implementation, a new bottleneck emerges: evaluating and fil

Temporal Coding as a Substrate for Sensorimotor Object Inference: A Spiking Reinterpretation of Thousand Brains Architecture

model-releasesarxiv-cs-ro

arXiv:2605.22206v1 Announce Type: cross Abstract: The Thousand Brains Theory (TBT) and its open-source Monty framework model object recognition through sensorimotor inference -- identifying objects by

Terminal Constraint Model Predictive Control for Image-Based Visual Servoing of UAVs with Kalman Filter-Based Moment Loss Compensation

arXiv:2605.22443v1 Announce Type: new Abstract: Image-Based Visual Servoing (IBVS) provides an efficient vision-guided control paradigm for unmanned aerial vehicles (UAVs) by directly regulating image

researcharxiv-cs-ro

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

The Double Dilemma in Multi-Task Radiology Report Generation: A Gradient Dynamics Analysis and Solution

arXiv:2605.22635v1 Announce Type: cross Abstract: While multi-task learning based automatic radiology report generation (RRG) is widely adopted to ensure clinical consistency, most focus on architectu

safetyarxiv-cs-cl

The Neglected Baseline in Model Interpretation

arXiv:2605.22417v1 Announce Type: new Abstract: We observe that existing model interpretation methods generally ignore the baseline, and such neglect often results in imprecise or even incorrect inter

Thermo-VL: Extending Vision-Language Models to Thermal Infrared Perception

arXiv:2605.21882v1 Announce Type: new Abstract: Vision-language models (VLMs) often fail under low illumination because their visual grounding is learned predominantly from RGB imagery, whereas therma

Time-varying rPPG signal separation via block-sparse signal model

arXiv:2605.22425v1 Announce Type: cross Abstract: Remote photoplethysmography (rPPG) enables non-contact measurement of cardiac pulse signals by analyzing subtle color changes in facial videos. Nevert

Token-Level LLM Collaboration via FusionRoute

arXiv:2601.05106v4 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit strengths across diverse domains. However, achieving strong performance across these domains with a singl

Token-weighted Direct Preference Optimization with Attention

arXiv:2605.21883v1 Announce Type: new Abstract: Direct Preference Optimization (DPO) aligns Large Language Models with human preferences without the need for a separate reward model. However, DPO trea

researcharxiv-cs-cl

Tokenisation via Convex Relaxations

arXiv:2605.22821v1 Announce Type: new Abstract: Tokenisation is an integral part of the current NLP pipeline. Current tokenisation algorithms such as BPE and Unigram are greedy algorithms -- they make

researcharxiv-cs-cl

Tokenization with Split Trees

arXiv:2605.22705v1 Announce Type: new Abstract: We introduce Tokenization with Split Trees (ToaST), a subword tokenization method that directly optimizes compression under a new recursive inference pr

Tool-Augmented Agent for Closed-loop Optimization,Simulation,and Modeling Orchestration

arXiv:2605.20190v1 Announce Type: new Abstract: Iterative industrial design-simulation optimization is bottlenecked by the CAD-CAE semantic gap: translating simulation feedback into valid geometric ed

agentsarxiv-cs-ai

Towards Clinically Interpretable Ophthalmic VQA via Spatially-Grounded Lesion Evidence

arXiv:2605.22414v1 Announce Type: new Abstract: Visual Question Answering (VQA) holds great promise for clinical support, particularly in ophthalmology, where retinal fundus photography is essential f

Towards Initialization-free Calibrated Bundle Adjustment

arXiv:2506.23808v2 Announce Type: replace Abstract: A recent series of works has shown that initialization-free BA can be achieved using pseudo Object Space Error (pOSE) as a surrogate objective. The

Towards Selection of Large Multimodal Models as Engines for Burned-in Protected Health Information Detection in Medical Images

arXiv:2511.02014v2 Announce Type: replace Abstract: The detection of Protected Health Information (PHI) in medical imaging is critical for safeguarding patient privacy and ensuring compliance with reg

Training-Free Fine-Grained Semantic Segmentations in Low Data Regimes: A FungiTastic Baseline

arXiv:2605.22492v1 Announce Type: new Abstract: Fine-grained semantic segmentation requires both precise localization and discrimination between visually similar classes. In FungiTastic, this problem

Training-Trajectory-Aware Token Selection

arXiv:2601.10348v2 Announce Type: replace Abstract: Efficient distillation is a key pathway for converting expensive reasoning capability into deployable efficiency, yet in the frontier regime where t