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Computer Science & AI
Much of the new work in computer science and AI appears first as a preprint on arXiv. ReadSearch reads those listings every day, with papers OpenAlex files under the same subjects, and this page shows the newest it has, from machine learning and language to systems, theory and security.
The newest 1,000 papers, from 4 November 2026 to 5 November 2026: 1,000 arXiv preprints.
Newest papers, page 7
Unified Overview of Safety Certificate Functions: Techniques from Hamilton--Jacobi Reachability and Control Barrier Functions
Safety is a central concern in modern autonomous systems.Action-Conditioned VLM Monitoring for Autonomous Vehicle Semantic Anomalies
We study action-conditioned monitoring of autonomous-vehicle behavior in semantically unusual driving scenes.CST-Bench: Benchmarking Counterfactual Spatial Transition Reasoning with Causal Transition On-Policy Self-Distillation
Spatial reasoning is a fundamental capability of multimodal large language models (MLLMs), yet existing benchmarks mainly focus on static scene understanding.FlashOffloading: Low-Latency KV Cache Offloading for Long-Context LLM Serving
In large language model (LLM) serving systems, the key-value (KV) cache grows linearly with sequence length and concurrency, so long-context inference easily hits the high-bandwidth memory (HBM)…OptIMerge: Optimization-Based Merging of Diffusion Models
The arithmetic merging of weights from multiple task-specific models fine-tuned from a shared base model, commonly known as model souping, has emerged as a popular strategy for multi-task learning…Training-Free Predictive Spatio-Temporal Token Pruning for Few-Step Autoregressive Video Diffusion
Few-step autoregressive (AR) video diffusion models generate videos chunk by chunk and have made efficient video generation practical.SPARE: Fast Linear Attention Decoding with Compact Recurrent States
Linear attention reduces the quadratic sequence-length complexity of softmax attention by maintaining fixed-size recurrent states.Improving Long-Tail Detection via Layout-Instruction Conditioned Diffusion Synthesis
Synthetic data from diffusion models can improve object detection, but long-tail performance is still limited by scarce rare classes and inflexible conditioning (e.g., text-only or layout-only…The Memory Trap: Language Agents Overgeneralize from Benign Interactions
Language agents increasingly use persistent memory to record user preferences and procedures across sessions.MetricTrail: Revisiting the Power of Metric Depth and Local Optimization for Long-Sequence Streaming 3D Reconstruction
We present MetricTrail, a streaming system for accurate camera motion estimation and dense reconstruction from long monocular videos.SKIM: Pruning Large Language Model Agents via Selective Knowledge Informed Masking
Large Language Model (LLM) agents are increasingly deployed under structured generation, where grammar constraints enforce output format at inference time.Whole-Body Elasto-Geometrical Calibration of Wheeled Humanoid Robots Using a Shared-Waist Dual-Chain Model
Wheeled humanoid robots carry both arms on one actuated waist, usually without torque sensors, so the accuracy of both end-effectors depends on a single waist model.Provable Zeroth-Order Safe Exploration for Reinforcement Learning from Human Feedback
Safe reinforcement learning from human feedback (Safe-RLHF) seeks to improve helpfulness while satisfying harmlessness constraints.Guidance Is a Field, Not a Scalar: Interval-Integrated Classifier-Free Guidance for One-Step Video Generation
One-step generators built on MeanFlow synthesize a video in a single function evaluation, yet inherit a rigid treatment of classifier-free guidance (CFG): the guidance scale is frozen during…MambaTG: Candidate-Aware State Space Modeling for Future Link Prediction on Temporal Graphs
Future link prediction on temporal graphs involves both repeated interactions between previously connected node pairs and first-time interactions between pairs with no prior interaction.ACSeL: Adaptive Configuration Search for Hardware-Constrained LLM Inference
Serving large language models (LLMs) under tight memory and latency service-level objectives (SLOs), including on edge devices, requires jointly selecting the model size, batch size, quantization…Integrating Learned Priors through Prior-Space Reparameterization for Physically Based Inverse Rendering
Physically based inverse rendering decomposes appearance into materials and illumination, an ambiguous problem for which learned material predictions provide useful prior information.Georeferenced Cross-View 3D Reconstruction from Ground and Satellite Images
Georeferenced 3D reconstruction from ground images requires recovering not only the local scene geometry, but also localizing every camera center and 3D point in a geographic coordinate frame.Digital Security Under Compound Threats: Surveillance, Threat Reasoning, and Habituation Among North Korean Defectors in China
North Korean defectors residing in China face persistent uncertainty regarding digital security and privacy.Subspace Learning with Outlier Exposure for Out-of-Distribution Detection
Out-of-Distribution (OoD) detection is pivotal for reliable deployments of Deep Neural Networks (DNNs), aiming to distinguish anomalous samples from the In-Distribution (InD) data in training.
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