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Browse AI research papers and methods. Search paper profiles, read recorded summaries and follow source links for the full research.

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Use the summary to find relevant work, then read the original paper. Compare the method, evaluation setting, baselines and limitations with your own problem. Check whether code and datasets are available; a reported benchmark result may not transfer to your use case.

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  1. SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning Owkin The Yeo-Johnson (YJ) transformation is a standard parametrized per-feature unidimensional transform… 2022-10-04 published
  2. Security Assessment of DeepSeek Harness with A.I.G: Evaluating Resistance to Indirect Prompt Injection taaft We assess indirect prompt injection in DeepSeek Harness (DSH), using AI-Infra-Guard (A.I.G) to cons… 2026-08-17 published
  3. See the Change, Keep the Flow: Unsupervised Action Segmentation via Spectral-Temporal Representation Learning taaft Unsupervised action segmentation aims to discover latent action categories and their temporal organ… 2026-08-30 published
  4. See, Hypothesize, Validate: Multimodal Agentic Framework for Discovering Governing PDEs taaft Discovering governing partial differential equations (PDEs) from observational data remains a core… 2026-08-28 published
  5. SeeClear: Reliable Transparent Object Depth Estimation via Generative Opacification taaft Monocular depth estimation remains challenging for transparent objects, where refraction and transm… 2026-03-20 published
  6. Seed-Anchored Budget-Bounded Graph Rendering for Question Answering on Industry-Standard Power-Grid Information and Exchange Models taaft Large language model question answering over power-grid models must respect a fixed context budget.… 2026-09-02 published
  7. Seeing Beyond the Lesion: Disease Recognition from Reactive CNS Tissue taaft Sampling error yields exclusively reactive, non-lesional brain parenchyma in a significant proporti… 2026-09-02 published
  8. Seeing Through Extreme Visual Sparsity: Surface Understanding from a Single Random Visual Patch taaft Surface material recognition from incomplete visual observations remains a challenging problem in r… 2026-08-30 published
  9. Segment Anything Meta Platforms We introduce the Segment Anything (SA) project: a new task, model, and dataset for image segmentati… 2023-04-05 published
  10. Segmentation of Bovid Dentition Under Imperfect Annotations: A Comparative Study of Convolutional and Attention Models taaft Semantic segmentation decomposes an image into distinct mask regions corresponding to different obj… 2026-08-31 published
  11. Segmentation-Based Attention Entropy: Detecting and Mitigating Object Hallucinations in Large Vision-Language Models Chongqing Chang’an Technology Large Vision-Language Models (LVLMs) achieve strong performance on many multimodal tasks, but objec… 2026-03-17 published
  12. SegVGGT: Joint 3D Reconstruction and Instance Segmentation from Multi-View Images taaft 3D instance segmentation methods typically rely on high-quality point clouds or posed RGB-D scans,… 2026-03-20 published
  13. SeisMamba: Low-Latency Single-Station Seismic Magnitude Estimation for Spatially Distributed Earthquake Early Warning taaft Rapid earthquake magnitude estimation is central to earthquake early warning, yet many operational… 2026-08-25 published
  14. SELECT: SELEctive Context Transfer for Class-Incremental Semantic Segmentation taaft Class-Incremental Semantic Segmentation (CISS) is fundamentally challenged by catastrophic forgetti… 2026-08-31 published
  15. Selection, Representation, and Execution in Sparse Fourier Neural Operators taaft Sparse representations are often expected to make models smaller and also reduce inference cost. Fo… 2026-08-30 published
  16. Selective Agent Guidance via Entropy: Learning Autonomous Policies from Imperfect VLM Teachers taaft Vision-Language Models (VLMs) provide useful priors for interactive decision-making, but using them… 2026-09-01 published
  17. Selective Hypergraph Refinement for Frozen Graph Clustering taaft Existing graph-clustering methods typically improve clustering performance by optimizing model para… 2026-09-03 published
  18. Selective Knowledge Edit Reversal via Gated Singular Vector Shrinkage taaft Knowledge editing provides an efficient way to update factual knowledge in large language models. H… 2026-09-02 published
  19. Selective Regenerative Decoding: Trajectory-Level Intervention for Inference-Time Reasoning taaft Inference-time decoding methods improve LLM reasoning by exploring multiple candidate trajectories,… 2026-08-25 published
  20. Self-Correcting Long-Horizon Search Agents via Tree-Structured Memory taaft Large language model (LLM)-based search agents answer questions through multi-step interactions wit… 2026-08-11 published
  21. Self-Evolving Agent Harnesses via Gated Semantic Quality-Diversity taaft Large Language Models (LLMs) have enabled capable agents across diverse applications. Beyond the fo… 2026-07-15 published
  22. Self-Explainable Multi-Label Graph Neural Network for Correlated Evidence Attribution taaft Multi-label graph learning intends to capture the intrinsic complexity of real-world applications,… 2026-08-27 published
  23. Self-Normalized Inference for Constant-Stepsize Temporal-Difference Learning under Markovian Sampling taaft Constant-stepsize temporal-difference (TD) learning is attractive for policy evaluation, but infere… 2026-08-11 published
  24. Self-Rewarding Language Models taaft We posit that to achieve superhuman agents, future models require superhuman feedback in order to p… 2024-01-18 published
  25. Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture Meta Platforms This paper demonstrates an approach for learning highly semantic image representations without rely… 2023-01-19 published
  26. Self-Supervised Lexical Representation Learning for Fast, Large-Scale Phylogenetic Inference taaft Computational phylogenetics has become an essential tool in historical linguistics, yet its applica… 2026-09-04 published
  27. Self-Supervised Pretext Tasks for Infant Cry Analysis: A Controlled Comparison and a Cautionary Result on Donateacry taaft We compare six self-supervised pretext tasks for infant cry analysis under a fixed budget, meaning… 2026-08-31 published
  28. SelfLift: Accelerating Few-Step Diffusion via Self-Recovering Resolution Transition taaft Few-step diffusion models substantially compress temporal computation, making the spatial cost of e… 2026-09-02 published
  29. Semantic Bayesian World Models taaft Knowledge graphs describe reality in crisp assertions, while the systems now consuming them, founda… 2026-09-03 published
  30. Semantic Head Specialization Guides Hybrid ViT Attention for Multimodal LLMs taaft Hybrid attention dominates frontier LLMs, yet Vision Transformers (ViTs) in multimodal LLMs lack a… 2026-08-28 published
  31. Semantic Signal-Assisted Inspection and Recovery Allocation in Reverse Logistics taaft Reverse-logistics operators often decide how to inspect and route returned assets before their cond… 2026-09-02 published
  32. Semantic-Aware Subgraph State Space Model for WSI Classification in Histopathology taaft Histopathological subtyping relies on the recognition of characteristic histological patterns. Thes… 2026-09-03 published
  33. Semantic-Spatial Discriminability Enhancement for Generalized Visual Grounding taaft Generalized Visual Grounding (GVG) task aims to localize targets in an image based on referring exp… 2026-08-31 published
  34. Semantics-Guided Automatic Tensorization for Multiobjective Evolutionary Algorithms: A Multi-Agent Framework taaft Multiobjective evolutionary algorithms (MOEAs) naturally expose population-level parallelism, but m… 2026-09-02 published
  35. Semi-structured multi-state delinquency model for mortgage default taaft We propose a semi-structured discrete-time multi-state model to analyse mortgage delinquency transi… 2026-03-27 published
  36. Semi-Supervised Classification with Graph Convolutional Networks taaft We present a scalable approach for semi-supervised learning on graph-structured data that is based… 2016-09-09 published