Recent Advances and Trends
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Recent Advances and Trends in Learning-based 3D Representations
arXiv:2606.04871v1 Announce Type: new Abstract: The selection of an appropriate 3D representation is a fundamental design decision that dictates the efficiency, quality, and capabilities of modern computer vision and graphics pipelines for tasks such as 3D reconstruction, novel-view synthesis and rendering, shape and motion analysis, recognition, and generation. While traditional representations (\eg meshes, point clouds, and volumetric grids) remain standard outputs of 3D sensors (\eg LiDAR...
Forecasting as Rendering: A 2D Gaussian Splatting Framework for Time Series Forecasting
Announce Type: replace Abstract: Time series forecasting remains a challenging problem due to the intricate entanglement of intra-period fluctuations and inter-period trends. While recent advances have attempted to reshape 1D sequences into 2D period-phase representations, they suffer from two principal limitations.
Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization
Announce Type: new Abstract: Recent advances in generative image editing have improved the realism and controllability of localized image manipulation, raising new challenges for image manipulation detection and localization (IMDL). However, existing IMDL benchmarks still have limitations in visual realism, manipulation diversity, and generator coverage, making it difficult to reflect recent trends in image manipulation. To address these limitations, we introduce Impostor, a high-quality...
MM-BizRAG: Rethinking Multimodal Retrieval-Augmented Generation for General Purpose Enterprise Q&A
arXiv:2606.04231v1 Announce Type: new Abstract: Recent advances in multimodal retrieval-augmented generation (MM-RAG) have shifted toward minimal parsing, relying on page-level images for producing retriever embeddings and for answer generation. While efficient, this trend often neglects explicit handling of the rich, structured information in complex enterprise documents, instead depending on pre-trained embeddings or vision-language models to implicitly capture such structure. In this...
Symbolic Regression for Shared Expressions: Introducing Partial Parameter Sharing
arXiv:2601.04051v3 Announce Type: replace Abstract: Symbolic regression aims to find symbolic expressions that describe datasets. Due to its inherent interpretability, symbolic regression (SR) is a powerful paradigm for scientific discovery. Recent advances have expanded SR to describe related phenomena using a single expression with varying sets of parameters, thereby introducing a single categorical variable.
Atlantic 'cold blob' may be reshaping Indian monsoon, steering rain northwest
Atlantic 'cold blob' may be reshaping Indian monsoon, steering rain northwest Lisa Lock Scientific Editor Robert Egan Associate Editor The Indian monsoon has shifted over the past quarter century. Northwest India now receives substantially more rain than it once did, while a lack of rain sends the Indo-Gangetic Plain toward drought.
When AI Builds Itself: Our progress toward recursive self-improvement
For most of AI’s history, humans drove every step in its development cycle. But at Anthropic, we are delegating a growing share of AI development to AI systems themselves, which is speeding up our work. Taken far enough, and given enough compute, that trend points to an AI system capable of fully autonomously designing and developing its own successor.
Iran’s proxies moving towards ‘violent gig economy’, but no imminent threat to Southeast Asia: Expert
Iran’s proxies moving towards ‘violent gig economy’, but no imminent threat to Southeast Asia: Expert While there are no reports of Iran-linked “violent gig economy” activities in Southeast Asia, “well-to-do” societies may be more vulnerable to threats, says a counterterrorism expert at a dialogue in Singapore. Iran’s proxy groups may be moving towards what can be described as a “violent gig economy”, with a shift from traditional militant cells to global external operations that are more...
Deep learning four decades of human migration
Abstract Human migration is a fundamental driver of global demographic change, shaping population structure, labour markets and social policy across countries1,2,3. Although long-term migration patterns are often linked to economic development4, they can shift rapidly in response to shocks such as conflict, environmental crises and political change5. Despite its importance, migration remains difficult to measure consistently: existing data are sparse, concentrated in high-income settings and...
A Cookbook of 3D Vision: Data, Learning Paradigms, and Application
arXiv:2606.04291v1 Announce Type: new Abstract: 3D vision has rapidly evolved, driven by increasingly diverse data representations, learning paradigms, and modeling strategies. Yet the field remains fragmented across representations and benchmarks, making it difficult to develop unified perspectives on efficiency, fidelity, and scalability. This work provides a data-centric taxonomy of 3D vision that connects geometric representations, datasets, learning frameworks, and applications within a...