WildBox provides over 237k 3D wildlife annotations from drone video and benchmarks reveal zero-shot 3D detection at 0 AP but fine-tuned performance of 8.68 AP-BEV and 13.17 AP3D, with depth estimation causing most errors.
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Emogen: Emotional image content generation with text-to-image diffusion models
Canonical reference. 91% of citing Pith papers cite this work as background.
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SpheRoPE modifies rotary position embeddings in diffusion transformers to enforce spherical topology for zero-shot 360 panorama generation across multiple backbones.
RESOLVE provides a controlled multi-resolution LiDAR and camera benchmark for evaluating 3D detection and tracking under point sparsity variations in roadside cooperative perception.
A method to decompose 3D Gaussian splats into independent albedo and shading components for consistent texture editing in radiance fields.
An asynchronous architecture decouples incremental voxel-based mapping from VLM-based semantic enrichment to produce queryable open-vocabulary 3D scene graphs that match or exceed prior methods on segmentation and grounding benchmarks.
MLLMs drop from over 85% accuracy on action presence to under 50% on matched action-denial videos, exposing a causal verification gap that causal graph prompts partially close.
A regularization technique that treats diffusion model outputs as a similarity kernel during material optimization in inverse rendering, enabling joint reconstruction of geometry, materials, and illumination that satisfies the rendering equation and generalizes to new lighting.
Introduces VG-GUIBench benchmark and TASKER keyframe extraction algorithm that improves performance on VideoQA and video-guided agentic tasks.
ScaLe-INR is a multi-branch INR architecture that applies directional scaling per the Fourier inverse theorem and a directional edge guidance loss to disentangle scales and improve reconstruction fidelity.
MATCH is the first flow matching method for multi-view anomaly detection, reporting SOTA results on Real-IAD and the first comprehensive evaluation on MANTA-Tiny while enabling real-time use by omitting the divergence term.
GeoFidelity-Bench shows text-to-image models gain city-level plausibility from local names but achieve near-zero improvement in exact segment identity, with GPS coordinates adding no benefit.
Arbor attaches constraint mesh tokens to a frozen text-to-3D denoiser to enable controllable generation obeying hull, avoidance, and touch constraints.
Target dynamics provide an intrinsic source of variation equivalent to controlled illumination changes, enabling scattering-compensated reconstruction of dynamic scenes with one acquisition per frame in holographic and fluorescence imaging.
The paper defines the 4DVLT task for worldline-centered 4D scene understanding, releases Instruct-4D with 129.4K QA pairs, and presents 4DTrack achieving 62.68 TGA_Top1, outperforming adapted baselines by 19.62 points.
FLM-Occ reformulates indoor occupancy prediction as feed-forward likelihood maximization over a mixture model with volume-normalized weights, achieving superior accuracy on Occ-ScanNet using only 32 superquadrics.
HERO maps DNA methylation and miRNA to a 16-dimensional intent vector for TF-IDF caption retrieval and cosine-gated repair in VLM-based multi-task breast cancer prediction, claiming SOTA on TCGA-BRCA.
StylisticBias benchmark shows 15 visual attributes explain nearly 80% of bias variation in six MLLMs by isolating single cues like age and fashion in generated images.
CloudLULC-Net is an end-to-end heterogeneous SAR-optical fusion network for LULC mapping under cloud contamination that achieves 86.60% OA, 83.29% F1, and 73.51% mIoU on a new global benchmark of 40,223 samples.
A two-stage generative model (Graph CVAE + flow matching) learns topology-agnostic motion codes from a new 5k-topology dataset and retargets video motion to arbitrary unseen skeletons.
FisherAdapTune uses temporal drift in Fisher geometry, measured by scale-invariant Jensen-Shannon distance, to progressively freeze stabilized parameter groups during fine-tuning, reporting gains on segmentation and zero-shot transfer.
An ILP-based oracle applied to seven VIS methods on YouTube-VIS and OVIS shows tracking instability as the dominant bottleneck, producing gaps exceeding 20 AP under occlusion while classification impact is secondary.
Attributed Feature Graphs (AFGs) represent CAD features as attributed nodes and relations as directed edges to enable GNN surrogate models that predict design performance with feature-level interpretability on the CarHoods10K dataset.
Empirical study of five LVR variants finds cosine alignment negatively correlates with accuracy (r=-0.94), supervised latents are bypassed under corruption (max 4-point shift), and answers are decodable downstream but not at the latent.
OTP-FM extends conditional flow matching by incorporating dynamic optimal transport potentials to enable efficient multimarginal transport learning with intermediate observed marginals.
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From Noise to Control: Parameterized Diffusion Policies
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Interaction Locality in Hierarchical Recursive Reasoning
Interaction locality is introduced as a task-geometry-aware measurement framework showing that high-level states in recursive models write locally while recursive updates build broader structures on maze, Sudoku, ARC-AGI, and 3D grounding tasks.
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Diagnosing Failure Modes of Shared-State Collaboration in Resource-Constrained Visual Agents
Introduces CoSee auditing framework and identifies Noise Reinforcement and Policy Collapse as dominant failure modes when weak 4B-8B models use shared state for multi-page visual QA.
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GRACE: Gradient-aligned Reasoning Data Curation for Efficient Post-training
GRACE scores reasoning steps via gradient alignment and trajectory consistency to select data subsets that match full performance with 5% of the data on Qwen3-VL-2B-Instruct.
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Mirror, Mirror on the Wall: Can VLM Agents Tell Who They Are at All?
Stronger VLM agents use mirror reflections for self-identification in controlled 3D tests, while weaker ones inspect but fail to extract or correctly attribute self-relevant information.
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MM-Telco: Benchmarks and Multimodal Large Language Models for Telecom Applications
MM-Telco creates multimodal benchmarks for telecom and demonstrates that fine-tuned LLMs and VLMs achieve significant performance gains on domain-specific tasks.
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ASH: Agents that Self-Hone via Embodied Learning
ASH learns long-horizon embodied policies from unlabeled internet video via a self-improvement loop that trains an IDM on its own trajectories and extracts supervision plus key-moment memory from video.
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A Comprehensive Survey of Agents for Computer Use: Foundations, Challenges, and Future Directions
A survey of 87 agents for computer use and 33 datasets that introduces a three-dimensional taxonomy across domain, interaction, and agent perspectives and identifies six research gaps.
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Mitigating Object Hallucinations in Vision-Language Models through Region-Aware Attention Recalibration
A training-free region-aware attention recalibration strategy reduces object hallucinations in LVLMs on CHAIR, POPE, and MME benchmarks while preserving fluency.
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Valley3: Scaling Omni Foundation Models for E-commerce
Valley3 is an omni MLLM for e-commerce that uses a four-stage pre-training pipeline plus post-training for controllable reasoning and agentic search, outperforming baselines on e-commerce benchmarks while staying competitive on general ones.
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StepGuard: Guarding Web Navigation via Single-Step Calibration
StepGuard framework with DDPO and CANR claims SOTA navigation and answer accuracy on web benchmarks by switching policies and triggering reflection on low-confidence steps.
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Position: Don't Just "Fix it in Post": A Science of AI Must Study Training Dynamics
A science of AI requires theories of training dynamics to predict outcomes from early signals, intervene on trajectories, and design procedures that reliably produce desired capabilities, biases, robustness, and safety properties.