arXiv AI
Jul 14
Prompting-MammAlps: Fine-Grained Text-to-Video Retrieval for Camera-Trap Data
arXiv:2607. 09876v1 Announce Type: cross Abstract: Automatically retrieving videos from large camera-trap datasets remains challenging.
Multimodal models
Vision-language models, speech and cross-modal systems that read, look and listen in the same forward pass.
arXiv AI
Jul 14
ActiveFly-Bench: Aligning Embodied Question Answering with Vision-Language-Action for Aerial Embodied Perception
arXiv:2607. 10180v1 Announce Type: cross Abstract: We introduce ActiveFly-Bench, the first benchmark to bridge cyberspace reasoning and physical-world interaction for UAV embodied perception.
arXiv AI
Jul 14
Lesioned Multimodal Language Models Reproduce Aphasic Picture-Naming Patterns
arXiv:2607. 11621v1 Announce Type: new Abstract: Aphasia following stroke commonly produces systematic naming errors with characteristic profiles, but whether general-purpose language models not designed for clinical simulation can reproduce these patterns remains untested.
arXiv Machine Learning
Jul 14
From Direction to Magnitude: How Multimodal Instruction-Tuning Reorganizes the Geometric Encoding of Identity-Specifying Prompts in Transformer Hidden States
arXiv:2607. 09842v1 Announce Type: new Abstract: We investigate whether identity-specifying system prompts produce statistically distinguishable geometric fingerprints in the hidden-state trajectories of four open-weight transformer language models spanning four post-training regimes: no training (Gemma-4-E4B base), multimodal RLHF (Gemma-4-E4B-it), RL distillation (DeepSeek-R1-Distill-Qwen-7B), and SFT (Qwen2.
arXiv Machine Learning
Jul 14
NMIRacle: Multi-modal Generative Molecular Elucidation from IR and NMR Spectra
arXiv:2512. 19733v3 Announce Type: replace-cross Abstract: Molecular structure elucidation from spectroscopic data is a long-standing challenge in Chemistry, traditionally requiring expert interpretation.
arXiv AI
Jul 14
Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model
arXiv:2607. 11643v1 Announce Type: cross Abstract: Recent foundation image and video generation models offer strong generalization and controllability, but their direct application to embodied scenarios is limited by requirements for multi-view consistency, geometric coherence, and robot embodiment constraints.
arXiv AI
Jul 14
StructAgent: Harness Long-horizon Digital Agents with Unified Causal Structure
arXiv:2607. 11388v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) and vision-language models (VLMs) have enabled increasingly capable digital agents for computer use.
arXiv AI
Jul 14
Context-Dependent Affordance Computation in Vision-Language Models
arXiv:2603. 04419v2 Announce Type: replace-cross Abstract: We characterize the phenomenon of context-dependent affordance computation in vision-language models (VLMs).
arXiv Machine Learning
Jul 14
Safe responses matter: Output-aware safety guardrail mitigate over-refusal in MLLMs
arXiv:2607. 09697v1 Announce Type: new Abstract: Existing safety mechanisms for multimodal large language models (MLLMs) face a fundamental trade-off between safety and utility.
arXiv AI
Jul 14
UNIT: Unleash Large Language Models Potential for Graph Continual Learning
arXiv:2607. 10159v1 Announce Type: new Abstract: In real-world multimodal web scenarios, graph-structured data often arrives in a streaming manner, making graph continual learning a crucial paradigm for continuously modeling such evolving structures.
arXiv Machine Learning
Jul 14
TabPFN beyond Tabular Data: Calibration and Accuracy on Multimodal Embeddings
arXiv:2607. 11007v1 Announce Type: new Abstract: Few-shot multimodal classification commonly attaches a lightweight head, such as $k$-nearest neighbors, logistic regression, or a linear SVM, to a frozen pretrained encoder.
arXiv Machine Learning
Jul 14
Generative Testing of Automated Speech Recognition Systems
arXiv:2607. 09833v1 Announce Type: cross Abstract: Automatic speech recognition (ASR) systems have achieved high accuracy with transformer-based models, enabling deployment in critical applications.
arXiv Machine Learning
Jul 14
Multimodal rumor detection enhanced by external evidence and forgery features
arXiv:2601. 14954v3 Announce Type: replace Abstract: Social media increasingly disseminates information through mixed image text posts, but rumors often exploit subtle inconsistencies and forged content, making detection based solely on post content difficult.
arXiv Machine Learning
Jul 14
CoGenCast: A Coupled Autoregressive-Flow Generative Framework for Time Series Forecasting
arXiv:2602. 03564v2 Announce Type: replace Abstract: Time series forecasting can be viewed as a generative problem that requires both semantic understanding over contextual conditions and stochastic modeling of continuous temporal dynamics.
arXiv AI
Jul 14
MG$^2$-RAG: Multi-Granularity Graph for Multimodal Retrieval-Augmented Generation
arXiv:2604. 04969v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) mitigates hallucinations in Multimodal Large Language Models (MLLMs), yet existing systems struggle with complex cross-modal reasoning.
arXiv AI
Jul 14
VehAnchor: Metadata-Free Metric Scale Recovery from Vehicle Cues in Aerial Imagery
arXiv:2603. 04277v2 Announce Type: replace-cross Abstract: Autonomous aerial robots operating in GPS-denied or communication-degraded environments frequently lose access to camera metadata and telemetry, leaving onboard perception systems unable to recover the absolute metric scale of the scene.
arXiv AI
Jul 14
Towards Predictive, Aligned, and Scalable Robot Learning
arXiv:2607. 11270v1 Announce Type: cross Abstract: Learning, at its core, extends beyond memorization to the ability to reason and solve novel problems by navigating a space of possibilities.
arXiv AI
Jul 14
The evolution of AI from image interpretation toward scientific inference in nanoparticle electron microscopy
arXiv:2607. 10388v1 Announce Type: cross Abstract: Artificial intelligence (AI) is transforming electron microscopy by enabling quantitative analysis of increasingly large and complex datasets for nanoparticle characterization.
arXiv AI
Jul 14
PivotMerge: Bridging Heterogeneous Multimodal Pre-training via Post-Alignment Model Merging
arXiv:2604. 22823v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) rely on multimodal pre-training over diverse data sources, where different datasets often induce complementary cross-modal alignment capabilities.
arXiv AI
Jul 14
IntentVLA: Short-Horizon Intent Modeling for Aliased Robot Manipulation
arXiv:2605. 14712v2 Announce Type: replace-cross Abstract: Robot imitation data are often multimodal: similar visual-language observations may be followed by different action chunks because human demonstrators act with different short-horizon intents, task phases, or recent context.