AI & Machine Learning · Computer Science & AI
Artificial Intelligence
The newest papers in Artificial Intelligence 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 11 October 2026 to 5 November 2026: 4,993 arXiv preprints and 7 OpenAlex records.
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Newest papers, page 21
CaliSplat: Sparse Gaussian Fitting and Calibrated Rate Allocation for Image Compression
2D Gaussian representations provide an explicit and lightweight alternative for image representation, enabling fast deterministic decoding without a heavy neural synthesis network.Verifier strength does not buy discovery quality: a pre-registered two-domain test of LLM-based automated research, with post-hoc evidence pointing to proposer-pool composition
Automated research pipelines pair an LLM proposer with a verifier on an implicit bet: discovery quality rises with verification strength.Formalizing PTX in Lean to Prove GPU Kernel Correctness
We present an approach to mathematically formalizing PTX, an approach that allows modeling and reasoning about patterns common in GPU kernels for Deep Learning, including acquire-release, tensor…Large Language Model-Assisted Adaptive Heuristic Search for Agile Earth Observation Satellite Scheduling
Agile Earth observation satellites must coordinate imaging tasks within limited observation windows, while accounting for attitude maneuvering and onboard energy constraints.$τ$-Rec-Books: A Disclosure-Controlled Benchmark for Requirement Elicitation in Agentic Recommender Systems
While conversational recommendation systems provide a more natural user interface, they face the challenge of progressively discovering a user's needs before they can recommend an item that…SaMA: Morpho Adaptation via Asymmetric Expansion of Kronecker Product
Low-rank adaptation (LoRA) has attracted significant attention in the parameter-efficient fine-tuning (PEFT) landscape.From Watching to Steering: Enabling Human-Coding Agent Collaboration through Execution Traces
Recent advances in large language models (LLMs) have enabled coding agents to autonomously perform complex software development tasks, yet their long-running execution remains difficult for users to…Treating the Symptom, Missing the Cause: Anatomy of a Scientific Reasoning Failure
Scientific agents can find interventions that work without understanding why they do.A Parametric Linear Conic Projection for Structured Sparse Attention
In this paper, we introduce the Cone Alignment Index (CAI), a scale-invariant sparsity measure associated with a Lorentz-cone geometry.Goal-Driven Autonomous Optical Experimentation via a Self-Recursive Hardware-Software Harness
We propose goal-driven self-recursive optical research in which agents use physical evidence to revise the hardware, software, models, and protocols used to pursue a scientific goal.CogniLife: Continuous Cognitive Distillation for Deployed Multi-Expert Agent Marketplaces
Multi-expert agent marketplaces -- where creators publish domain-specific AI experts for end users to consult -- are an emerging deployment pattern for language technology.Reconstruction-Based Diagnosis through Gödel-Regularized Virtual Observability
Not every component in a technical system can be equipped with sensors.Perseus: A Full-Stack System for Homomorphic Model Inference
Large Language Models (LLMs) have made it exceptionally convenient for users to send their private data to model providers, which process them in plaintext.Spatial Memory for AR Glasses: Hierarchical Visual Acquisition and Source-Linked Recall
We present a spatial-memory system that enables optical see-through AR glasses to recall earlier physical encounters.Signals: Continuous Diagnostics of AI Agents
AI agents can make incorrect decisions or waste resources even when their tools and infrastructure work normally.Fast, Cheap, and Fair? Evaluating Decision Models
Industries are increasingly adopting AI-driven systems to automate a wide range of tasks, including high-stakes decisions in human resources, such as candidate screening and recruitment.Learnings and Pitfalls from AI-Assisted A/B Experimentation at Scale
A/B testing underpins product decisions by providing trustworthy, reproducible quantification of proposed changes' effects.BtsPruner: Role-Aware Visual Token Pruning for Large Vision-Language Models
Large Vision-Language Models (LVLMs) often process hundreds or thousands of visual tokens, resulting in substantial computational and memory overhead during inference.CANDO: Conservative Action-Noise Directional Optimization for Residual Reinforcement Learning
Pretrained generative policies provide strong behavior priors for robot control, but adapting them efficiently with online reinforcement learning remains difficult.Are LLM Assistants Regulatory Ready? Answers from regenold's 2026 EU AI Act Q&A Challenge
Large language model (LLM) assistants are increasingly proposed for regulatory affairs, yet their reliability in regulatory tasks remains unclear.