aoiandroid/papers

📚 Authoritative AI Research & Projects Report

Generated: 2026-05-17 16:16:40 UTC Repository Destination: aoiandroid/papers

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🏆 Top Hugging Face Daily Papers

Curated list of the most highly upvoted recent research papers on Hugging Face Hub.

[🔥 0 Upvotes] Aligning Latent Geometry for Spherical Flow Matching in Image Generation

Latent flow matching for image generation usually transports Gaussian noise to variational autoencoder latents along linear paths. Both endpoints, however, concentrate in thin spherical shells, and a Euclidean chord leaves those shells even when preprocessing aligns their radii. By decomposing each latent token into radial and angular components, w...

[🔥 0 Upvotes] WildTableBench: Benchmarking Multimodal Foundation Models on Table Understanding In the Wild

Using multimodal foundation models to analyze table images is a high-value yet challenging application in consumer and enterprise scenarios. Despite its importance, current evaluations rely largely on structured-text tables or clean rendered images, leaving the visual complexity of in-the-wild table images underexplored. Such images feature varied ...

[🔥 0 Upvotes] Long Context Pre-Training with Lighthouse Attention

Training causal transformers at extreme sequence lengths is bottlenecked by the quadratic time and memory of scaled dot-product attention (SDPA). In this work, we propose Lighthouse Attention, a training-only symmetrical selection-based hierarchical attention algorithm that wraps around ordinary SDPA and can be easily removed towards the end of the...

[🔥 0 Upvotes] Boosting Reinforcement Learning with Verifiable Rewards via Randomly Selected Few-Shot Guidance

Reinforcement Learning with Verifiable Rewards (RLVR) has achieved great success in developing Large Language Models (LLMs) with chain-of-thought rollouts for many tasks such as math and coding. Nevertheless, RLVR struggles with sample efficiency on difficult problems where correct rollouts are hard to generate. Prior works propose to address this ...

[🔥 0 Upvotes] PreScam: A Benchmark for Predicting Scam Progression from Early Conversations

Conversational scams, such as romance and investment scams, are emerging as a major form of online fraud. Unlike one-shot scam lures such as fake lottery or unpaid toll messages, they unfold through multi-turn conversations in which scammers gradually manipulate victims using evolving psychological techniques. However, existing research mainly focu...

[🔥 0 Upvotes] Sat3DGen: Comprehensive Street-Level 3D Scene Generation from Single Satellite Image

Generating a street-level 3D scene from a single satellite image is a crucial yet challenging task. Current methods present a stark trade-off: geometry-colorization models achieve high geometric fidelity but are typically building-focused and lack semantic diversity. In contrast, proxy-based models use feed-forward image-to-3D frameworks to generat...

[🔥 0 Upvotes] Learning to Communicate Locally for Large-Scale Multi-Agent Pathfinding

Multi-agent pathfinding (MAPF) is a widely used abstraction for multi-robot trajectory planning problems, where multiple homogeneous agents move simultaneously within a shared environment. Although solving MAPF optimally is NP-hard, scalable and efficient solvers are critical for real-world applications such as logistics and search-and-rescue. To t...

[🔥 0 Upvotes] ViMU: Benchmarking Video Metaphorical Understanding

Any new medium, once it emerges, is used for more than the transmission of overt content alone. The information it carries typically operates on two levels: one is the content directly presented, while the other is the subtext beneath it-the implicit ideas and intentions the creator seeks to convey through the medium. Likewise, since video technolo...

[🔥 0 Upvotes] Boosting Omni-Modal Language Models: Staged Post-Training with Visually Debiased Evaluation

Omni-modal language models are intended to jointly understand audio, visual inputs, and language, but benchmark gains can be inflated when visual evidence alone is enough to answer a query. We study whether current omni-modal benchmarks separate visual shortcuts from genuine audio-visual-language evidence integration, and how post-training behaves ...

[🔥 0 Upvotes] BEAM: Binary Expert Activation Masking for Dynamic Routing in MoE

Mixture-of-Experts (MoE) architectures enhance the efficiency of large language models by activating only a subset of experts per token. However, standard MoE employs a fixed Top-K routing strategy, leading to redundant computation and suboptimal inference latency. Existing acceleration methods either require costly retraining with architectural ch...

[🔥 0 Upvotes] LiSA: Lifelong Safety Adaptation via Conservative Policy Induction

As AI agents move from chat interfaces to systems that read private data, call tools, and execute multi-step workflows, guardrails become a last line of defense against concrete deployment harms. In these settings, guardrail failures are no longer merely answer-quality errors: they can leak secrets, authorize unsafe actions, or block legitimate wor...

[🔥 0 Upvotes] Realiz3D: 3D Generation Made Photorealistic via Domain-Aware Learning

We often aim to generate images that are both photorealistic and 3D-consistent, adhering to precise geometry, material, and viewpoint controls. Typically, this is achieved by fine-tuning an image generator, pre-trained on billions of real images, using renders of synthetic 3D assets, where annotations for control signals are available. While this a...

[🔥 0 Upvotes] FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale

Many real-world coding challenges are open-ended and admit no known optimal solution. Yet, recent progress in LLM coding has focused on well-defined tasks such as feature implementation, bug fixing, and competitive programming. Open-ended coding remains a weak spot for LLMs, largely because open-ended training problems are scarce and expensive to c...

[🔥 0 Upvotes] CurveBench: A Benchmark for Exact Topological Reasoning over Nested Jordan Curves

We introduce CurveBench, a benchmark for hierarchical topological reasoning from visual input. CurveBench consists of 756 images of pairwise non-intersecting Jordan curves across easy, polygonal, topographic-inspired, maze-like, and dense counting configurations. Each image is annotated with a rooted tree encoding the containment relations between ...

[🔥 0 Upvotes] Adaptive Teacher Exposure for Self-Distillation in LLM Reasoning

On-policy self-distillation has become a strong recipe for LLM reasoning, where a privileged teacher supervises the student's own rollouts while conditioning on the reference solution. A design choice shared by nearly all such methods, however, has gone unquestioned: the teacher always sees the full reference reasoning. We argue that this default i...

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🔬 Latest Authoritative ArXiv Research

Key breakthroughs in Artificial Intelligence, NLP, Computer Vision, and Machine Learning.

EntityBench: Towards Entity-Consistent Long-Range Multi-Shot Video Generation

• Authors: Ruozhen He, Meng Wei, Ziyan Yang, Vicente Ordonez
• Published: 2026-05-14

  Abstract: Multi-shot video generation extends single-shot generation to coherent visual narratives, yet maintaining consistent characters, objects, and locations across shots remains a challenge over long sequences. Existing evaluations typically use independently generated prompt sets with limited entity coverage and simple consistency metrics, making stand...

ATLAS: Agentic or Latent Visual Reasoning? One Word is Enough for Both

• Authors: Ziyu Guo, Rain Liu, Xinyan Chen, Pheng-Ann Heng
• Published: 2026-05-14

  Abstract: Visual reasoning, often interleaved with intermediate visual states, has emerged as a promising direction in the field. A straightforward approach is to directly generate images via unified models during reasoning, but this is computationally expensive and architecturally non-trivial. Recent alternatives include agentic reasoning through code or to...

RefDecoder: Enhancing Visual Generation with Conditional Video Decoding

• Authors: Xiang Fan, Yuheng Wang, Bohan Fang, Zhongzheng Ren
• Published: 2026-05-14

  Abstract: Video generation powers a vast array of downstream applications. However, while the de facto standard, i.e., latent diffusion models, typically employ heavily conditioned denoising networks, their decoders often remain unconditional. We observe that this architectural asymmetry leads to significant loss of detail and inconsistency relative to the i...

VGGT-$Ω$

• Authors: Jianyuan Wang, Minghao Chen, Shangzhan Zhang, Nikita Karaev
• Published: 2026-05-14

  Abstract: Recent feed-forward reconstruction models, such as VGGT, have proven competitive with traditional optimization-based reconstructors while also providing geometry-aware features useful for other tasks. Here, we show that the quality of these models scales predictably with model and data size. We do so by introducing VGGT-$Ω$, which substantially imp...

Aligning Latent Geometry for Spherical Flow Matching in Image Generation

• Authors: Tuna Han Salih Meral, Kaan Oktay, Hidir Yesiltepe, Adil Kaan Akan
• Published: 2026-05-14

  Abstract: Latent flow matching for image generation usually transports Gaussian noise to variational autoencoder latents along linear paths. Both endpoints, however, concentrate in thin spherical shells, and a Euclidean chord leaves those shells even when preprocessing aligns their radii. By decomposing each latent token into radial and angular components, w...

RAVEN: Real-time Autoregressive Video Extrapolation with Consistency-model GRPO

• Authors: Yanzuo Lu, Ronglai Zuo, Jiankang Deng
• Published: 2026-05-14

  Abstract: Causal autoregressive video diffusion models support real-time streaming generation by extrapolating future chunks from previously generated content. Distilling such generators from high-fidelity bidirectional teachers yields competitive few-step models, yet a persistent gap between the history distributions encountered during training and those ar...

FutureSim: Replaying World Events to Evaluate Adaptive Agents

• Authors: Shashwat Goel, Nikhil Chandak, Arvindh Arun, Ameya Prabhu
• Published: 2026-05-14

  Abstract: AI agents are being increasingly deployed in dynamic, open-ended environments that require adapting to new information as it arrives. To efficiently measure this capability for realistic use-cases, we propose building grounded simulations that replay real-world events in the order they occurred. We build FutureSim, where agents forecast world event...

Articraft: An Agentic System for Scalable Articulated 3D Asset Generation

• Authors: Matt Zhou, Ruining Li, Xiaoyang Lyu, Zhaomou Song
• Published: 2026-05-14

  Abstract: A bottleneck in learning to understand articulated 3D objects is the lack of large and diverse datasets. In this paper, we propose to leverage large language models (LLMs) to close this gap and generate articulated assets at scale. We reduce the problem of generating an articulated 3D asset to that of writing a program that builds it. We then intro...

VGGT-Edit: Feed-forward Native 3D Scene Editing with Residual Field Prediction

• Authors: Kaixin Zhu, Yiwen Tang, Yifan Yang, Renrui Zhang
• Published: 2026-05-14

  Abstract: High-quality 3D scene reconstruction has recently advanced toward generalizable feed-forward architectures, enabling the generation of complex environments in a single forward pass. However, despite their strong performance in static scene perception, these models remain limited in responding to dynamic human instructions, which restricts their use...

Quantitative Video World Model Evaluation for Geometric-Consistency

• Authors: Jiaxin Wu, Yihao Pi, Yinling Zhang, Yuheng Li
• Published: 2026-05-14

  Abstract: Generative video models are increasingly studied as implicit world models, yet evaluating whether they produce physically plausible 3D structure and motion remains challenging. Most existing video evaluation pipelines rely heavily on human judgment or learned graders, which can be subjective and weakly diagnostic for geometric failures. We introduc...

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