AI & Machine Learning · Computer Science & AI
Machine Learning
The newest papers in Machine Learning that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 12 October 2026 to 5 November 2026: 5,000 arXiv preprints.
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Newest papers, page 46
LLM-Enhanced Multimodal House Price Prediction using Structured, Textual, and Visual Features
Accurate house price prediction is essential for real estate buyers, sellers, agents, and financial institutions.FinForesight: A Diagnostic Backtesting Benchmark for Deep Research Systems in Financial Forecasting
Anticipating financial outcomes requires synthesizing evolving evidence and reasoning under uncertainty, making deep research systems promising tools for forecasting.BanglishDepYT: Depression Detection in Native Bengali Social Media with Emotion-Preserving Preprocessing and Domain-Adaptive Pretraining
Depression affects millions of Bengali speakers across South Asia, yet automated detection systems have relied almost entirely on datasets translated from English.Sharp Generalization for Nonparametric Regression in Interpolation Space by Shallow Over-Parameterized Neural Networks with Channel Attention
We study nonparametric regression using an over-parameterized two-layer ReLU neural network with fixed covariance-based channel attention, trained by gradient descent with both layers updated…CREDO: Evidence-Conditioned Credit Assignment for Temporal Reasoning Agents
Temporal Knowledge Graph Question Answering (TKGQA) requires language model agents to retrieve evidence, select relevant facts, and perform multi-step temporal reasoning.Yielding Fairness: Coupled Learning and Fairness for Value-Weighted Ranking
Risk screening and recommendation systems pass or block accounts that generate both value and loss.Near-Optimal $\sqrt{K}$-Regret for Online Learning in Uninformed Markov Games
We study online learning in two-player uninformed Markov games, where the opponent may follow an arbitrary, unknown policy in each episode and the learner does not observe the opponent's actions…Physics-Informed One-Step Generation on Long-short flow maps
Physics-informed generative models should produce samples that are both data-aligned and physically valid, yet existing methods are often iterative and too slow for practical use.A Hybrid Anomaly Detection Method for Electric Vehicle Identification from Smart Meter Recordings
In recent years, electric vehicles (EVs) have attracted much attention due to their potential to decarbonize the transport system.A Hybrid Anomaly Detection Method for Multivariate Time Series
Multivariate time series are ubiquitous in monitoring smart systems such as power plants, smart houses, and servers.Stand-In Effects and Pooling Amplification: Design-Based Tests of Whether Biological World Models Use Actions
Action-conditioned world models are increasingly trained on data from randomized experiments, and whether their predictions respond to actions is usually checked by replacing or removing the actions…How Much Does Random Rotation Help GPTQ? Sharp Worst-Case Rate Gaps in the High-Rate Regime
GPTQ is Babai's nearest-plane algorithm on the lattice of the Cholesky factor of the layer's input second moment $Σ$.Xiaomi Auto World Model 2.0: Causal World Models for Real-World Driving and Embodied Intelligence
We present Xiaomi Auto World Model 2.0, a unified streaming causal world model for Physical AI.Wave Physics as Representation: Tensor-Structured Neural Reconstruction for Ocean Acoustic Fields
Reconstructing three-dimensional (3D) complex ocean acoustic fields from sparse measurements is challenging due to highly oscillatory wave structures and restricted sensing patterns/routes.Leveraging 2D Foundation Priors for Generalized Category Discovery under Test-Time Adaptation in 3D LiDAR Segmentation
In autonomous driving, 3D LiDAR semantic segmentation is expected to adapt to evolving environments and recognize previously unseen categories, making generalized category discovery under test-time…SEALECT: Scene-Conditioned Pose Priors for Plausible Maritime Vessel Retrieval
We address scene-conditioned object retrieval for compositional augmentation in maritime imagery, where strong geometric constraints make appearance-only retrieval produce physically implausible…Direct Covariance-to-Beamformer Mapping for Low-Latency Hybrid ISAC Beamforming with Subsequent DoA Estimation
Integrated sensing and communication (ISAC) systems typically employ a two-stage beamforming pipeline, in which target directions are first estimated from the received covariance matrix and then…SparseLift: Automatically Optimizing Opaque Sparse Paths in Industrial-Scale Recommendation Model Training
The sparse path, comprising sparse operations and collective communication, is a critical component of large-scale recommendation models.MatMoE: Matryoshka Mixture-of-Experts with Dynamic Mixed-Precision Quantization for Efficient Inference
Mixture-of-Experts (MoE) architecture has been widely adopted in large language models (LLMs) since it reduces the computational cost through sparse expert activation.Comparative Strategies for Handling Imbalanced QSAR Regression: A Case Study on hERG Activity Prediction
Data imbalance frequently occurs in QSAR modeling, yet most studies focus on classification tasks, and few address regression tasks, as it is challenging to determine which regions of the data are…