arXiv AI
Jul 28
Towards High-Level Semantic Intelligence
arXiv:2607. 24082v1 Announce Type: new Abstract: Recent advances in AI have substantially expanded its cognitive and reasoning capabilities.
Multimodal models
Vision-language models, speech and cross-modal systems that read, look and listen in the same forward pass.
arXiv AI
Jul 28
Multimodal Domain Generalization for Depression Detection: An Attention-Based BiLSTM Network with Domain-Adversarial Training
arXiv:2607. 22794v1 Announce Type: cross Abstract: Automatic depression detection with deep learning has shown promise but often suffers from limited generalization due to domain shift arising from inter-speaker variability.
arXiv AI
Jul 28
Spatial-IQ: Deconstructing Spatial Intelligence via Hierarchical Capability Tests
arXiv:2607. 22864v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) excel at visual interpretation but fail on spatial reasoning tasks that humans solve reliably.
arXiv AI
Jul 28
Chart Deception in Vision-Language Models: From Vulnerability to Mitigation
arXiv:2607. 22600v1 Announce Type: new Abstract: Information visualizations are widely used to communicate patterns, trends, and outliers, yet deceptive design choices-such as truncated or inverted axes, distorted aspect ratios, inappropriate encodings, and misleading color mappings-can systematically alter interpretation while preserving the underlying data.
arXiv AI
Jul 28
Novel Claim or D\'ej\`a Vu? Rethinking "Contamination-Free'' Dynamic Evaluation for Multimodal Automated Fact-Checking
arXiv:2607. 23514v1 Announce Type: cross Abstract: Multimodal automated fact-checking (MAFC) verifies claims by retrieving and reasoning over external evidence.
arXiv AI
Jul 28
WCM: World-Cognition Model for Generalizable Human-Robot Interaction
arXiv:2607. 22999v1 Announce Type: cross Abstract: Language agents can now interact fluently with users in software, but robots still struggle to bring comparable interaction to physical tasks.
arXiv Machine Learning
Jul 28
WorldDiT: A Unified Diffusion Architecture for World and Action Modeling
arXiv:2607. 23909v1 Announce Type: new Abstract: Many recent robot policies pursue stronger control by using large pretrained vision-language models (VLMs) as the action backbone.
arXiv AI
Jul 28
An Interactive Vision Language Platform for Cognitive Remediation in Schizophrenia
arXiv:2607. 22721v1 Announce Type: cross Abstract: Cognitive remediation tasks often require patients to perform structured actions involving object manipulation and sequential reasoning.
arXiv AI
Jul 28
CAPT: A Multi-task Continuous Autoregressive Transformer enabling Cross-dataset and Cross-species Transfer for Calcium Population Dynamics
arXiv:2607. 23258v1 Announce Type: new Abstract: Large-scale calcium imaging has created an opportunity to build foundation-style models for neural population dynamics, but a central question remains unresolved: \textbf{whether a model pretrained on one collection of recordings can generalize to new datasets, experimental paradigms, and even species.
arXiv AI
Jul 28
VlogReward: Learning Multi-Dimensional Evaluation for Vlog Editing
arXiv:2607. 22632v1 Announce Type: new Abstract: The rapid rise of vlogs as a personalized storytelling medium has created a demand for automated systems to evaluate and refine vlog editing plans.
arXiv AI
Jul 28
GOTS: Greedy Orthogonal Token Selection for High-Resolution Vision-Language Models
arXiv:2607. 23913v1 Announce Type: new Abstract: Modern vision-language models (VLMs) increasingly rely on dynamic or high-resolution visual encoding, producing thousands of visual tokens that substantially increase downstream language-model inference cost.
arXiv AI
Jul 28
DICA: Dual-Indicator Guided Contrastive Alignment in Multimodal Large Language Models
arXiv:2607. 23944v1 Announce Type: new Abstract: Human visual reasoning typically follows a coarse-to-fine attention process, starting from global scene understanding and gradually focusing on question-relevant regions.
arXiv AI
Jul 28
MM-ShiftKV: Decode-Aware Prefill-Stage KV Selection for Multimodal Large Language Models
arXiv:2607. 22586v1 Announce Type: new Abstract: Key-Value (KV) caching is essential for efficient inference in multimodal large language models (MLLMs), yet its memory footprint grows linearly with context length and becomes a major bottleneck due to the large number of visual tokens.
arXiv AI
Jul 28
Co-Learning for Missing Arbitrary Modalities in Multi-modal Classification
arXiv:2607. 24683v1 Announce Type: cross Abstract: Multi-modal classification leverages complementary information across diverse data sources to enhance predictive performance.
arXiv AI
Jul 28
Beyond Sequential Interaction: Benchmarking Parallel Execution and Coordination for GUI Agents
arXiv:2607. 22689v1 Announce Type: new Abstract: Graphical user interface (GUI) agents are systems powered by large multimodal models (LMMs).
arXiv AI
Jul 28
Reason Before You Retrieve: Agentic Planning for Multi-modal RAG
arXiv:2607. 22643v1 Announce Type: new Abstract: Multimodal retrieval-augmented generation (mRAG) aims to answer image-text queries with external knowledge, but most existing systems still retrieve directly from raw multimodal input over a flat evidence space.
arXiv AI
Jul 28
scMIR: a vision-language foundation model for single-cell light microscopy image representation
arXiv:2607. 22712v1 Announce Type: cross Abstract: Single-cell light microscopy images have become an important data source for characterizing cell phenotypes, but their complexity and heterogeneity pose challenges to high-throughput automated analysis.
arXiv Machine Learning
Jul 28
FedTaste: Topology-Aware Structural Transfer for Multimodal Federated Learning with Missing Modalities
arXiv:2607. 23245v1 Announce Type: cross Abstract: Multimodal Federated Learning is often challenged by arbitrary modality missingness and Non-IID data distributions, which lead to severe representation drift and hinder effective collaboration across clients.
arXiv AI
Jul 28
Generative Artificial Intelligence (GenAI) to convert images of queuing networks into verifiable simulation models: an open-weight LLM workflow approach
arXiv:2607. 24259v1 Announce Type: new Abstract: Recent work has explored the use of Large Language Models (LLMs) to automate simulation model building, typically by generating executable code directly from natural language descriptions.
arXiv Machine Learning
Jul 28
SimBEV2X: A Large-Scale Dataset and Data Generation Tool for Multi-Task Vehicle-to-Everything Cooperative Perception
arXiv:2607. 23910v1 Announce Type: cross Abstract: Cooperative perception through vehicle-to-everything (V2X) communication can overcome the inherent physical limitations of individual autonomous vehicles, such as occlusions and limited sensor range.