A field on ReadSearch
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 23
Accepted but Wrong: Silent Failures of LLM Code Repairs after API Migrations
After a runtime or API migration, an LLM-repaired procedure can run cleanly yet return wrong results, and a release check on typical test inputs ships it.DART: Domain-Agnostic Residual Transfer for Generalist Anomaly Detection
Generalist Anomaly Detection (GAD) aims to detect anomalies in unseen domains using only a few reference samples.Accelerating Safe Reinforcement Learning with Massive Parallelism
We investigate the problem of scaling safe reinforcement learning (safe RL) to massively parallel training regimes, where a large number of environments are exe- cuted with short rollout horizons.Aligning Policy Encoders with a Shape Teacher
3D-aware representations can improve robotic manipulation by providing geometric information that is robust to changes in viewpoint, object position, and occlusion.LeanContext: Disentangling Mathematical Resources from Local Formal Context in Lean Whole-Proof Generation
Neural theorem proving increasingly uses retrieved premises and project context to support proof generation.Multimodal-SEA: Benchmarking AI Agent Security under Multimodal Social Engineering Attacks
Personal AI agents face social engineering attacks supported by forged multimodal content, but existing evaluations mainly focus on text-based dialogue, leaving their intrinsic security under such…A Generative Model of Contextual Integrity: Appropriate vs. Inappropriate Information Sharing
Contextual integrity (CI) holds that appropriate information flow depends on context-specific norms.Hard Issue, Weak Model, or Bad Run? Rethinking Failure Prediction for Coding Agents
Trajectory-based failure predictors for software engineering (SE) agents read the partial trajectory of a run to flag whether it is going right or wrong.Interactive Visual Gym: Evaluating Visual Interaction Models with Simulated Users in Interactive Worlds
Visual interaction models that support users during ongoing physical tasks require evaluation in closed loop, where assistant responses can change subsequent user behavior and task outcomes.Hierarchical Incremental Beta Splatting for Online Reconstruction
Online 3D Gaussian Splatting reconstructs a scene during capture: each keyframe spawns primitives once and refines them for only a few dozen iterations, leaving little chance to fix poor…AutoCompress: Automated Hardware-Guided Model Compression
LLM pruning must preserve quality while meeting hardware- and workload-specific constraints on latency, throughput, and memory.ManimCode: Learning Visual Self-Correction for Educational Animation
Manim supports precise, programmatic video generation, but a successfully rendered educational animation can still have visual defects, missing explanations, or incorrect content.Transformer-Based Trajectory Prescription for sEMG-Optimizing Robot-Mediated Rehabilitation
Robot-mediated rehabilitation has the potential to deliver high-intensity, individualized therapy, but existing systems (which have not consistently improved outcomes) typically prescribe kinematic…Beyond Quantum Messages: Toward Quantum-Native Network Functioning
The Quantum Internet is commonly envisioned as a network that transports quantum states and distributes entanglement as the key resource underpinning distributed quantum applications.REACT: Towards Real-Time Completion of Skeletal Motion Signals
Tracking user motion in interactive and immersive applications is increasingly common (e.g., video games, XR systems, smartphones).Dynamic Optimistic Constrained OCO with Memory via Delay Equivalence
Online Convex Optimization with memory and time-varying constraints (COCO-M) is a recently-introduced framework that captures the dynamics of stateful online learning and non-stochastic control with…First-Token Attraction in Mamba Dynamics
We study token dynamics in deep Mamba models, with a particular focus on the attracting role of the first token.GINGER: Spicing Up Graph-Based Vector Search
We present \textsc{Ginger}, a state-of-the-art open-source C++ library for graph-based approximate nearest neighbor search (ANNS).Measured Coupling for Parallel Decoding in Diffusion Language Models
Diffusion language models can write many tokens per step, but must choose which tokens are safe to commit together.RM-VLM: From Natural-Language Task Descriptions to Vision-Grounded Reward Machines
Reward machines (RMs) have been proposed as a reward formulation in reinforcement learning (RL) to capture non-Markovian tasks where credit assignment depends on history.
Get the few papers worth your time in Computer Science & AI every morning.
Choose your topics and ReadSearch reads the new papers in them each day, then brings you the few worth reading, each with its key finding in a sentence.