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: 4,998 arXiv preprints and 2 OpenAlex records.
Get the few papers worth your time in Artificial Intelligence every morning.
Follow Artificial Intelligence and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 74
ChatGPT as a Surveillance Assistant? An Exploratory Case Study of AI-Assisted Surveillance Risks
Large language models (LLMs) can generate detailed guidance, functional code, and persuasive text at scale.TSFLab: A Self-Improving Agent-Agnostic Workbench for Time Series Forecasting Research
As publications and products on time series forecasting (TSF) proliferate, researchers face a growing burden of analyzing existing work.Does Recursive Knowledge Construction Help Agents Verify Consensus Claims in Science?
Recent scientific agents build knowledge recursively by retrieving evidence, constructing an intermediate state, and judging whether that state contains sufficient information.Towards Portable Specification of the Agent Harness
Large language models act only through the infrastructure that surrounds them.Agentic World Modeling for Agent Test-time Scaling without Environment Replica
Test-time scaling (TTS) improves large language model agents by sampling and selecting among multiple candidate trajectories, but common realizations assume that these trajectories can be executed…A Theoretical Framework for Understanding and Building "Any-task inference" Capable Foundation Models
In this work, we provide a formal framework and mathematical definition for the subset of foundation models focused on enabling the property of "any-task inference" (ATI) (similar to zero-shot…DiRAFT: Privacy-Aware Financial Transcript Synthesis from Aggregate Discourse Priors
Using customer conversations to train and evaluate financial language models raises confidentiality concerns because non-public financial facts can remain after direct identifiers are masked.The First Few Tokens Matter: Understanding Chain-of-Thought Controllability
Chain-of-thought (CoT) monitoring is a promising way to oversee increasingly capable agents.Benchmarking Forecasting Agents on Yesterday's Tomorrows
Digital agents can now gather and organize information, reason over it, and use tools to complete complex tasks.Kernel-based Interpolatory Methods for Context Compression of Attention Mechanisms
The bottleneck of attention mechanisms, which are the fundamental building block of modern language models, is their quadratic complexity in terms of context size.On the Origin and Evolution of Training-Inference Mismatch in LLM Reinforcement Learning
On-policy reinforcement learning for large language models assumes that training responses are sampled from the current policy.Opening the Box Changes the Cat: LLMs Detect Chain-of-Thought Monitoring - What now?
Chain-of-thought (CoT) reasoning allows large language models (LLMs) to generate intermediate reasoning traces in natural language while solving complex tasks.CAMEL: Cross-Architecture Masked Embedding Learning for Ultra-Lightweight Retinal Foundation Models
Recent progress in deep learning has substantially advanced automated grading of ophthalmologic pathologies, supported by large annotated datasets and improved representation learning.P-ContextBench: From Personal Fact Recall to Personalized Agent Behavior
Large language models (LLMs) are increasingly used for personal tasks, yet evaluating their safe use of personal context remains difficult because such contexts are private, fragmented, dynamic, and…Nedimo: An Evidence-Grounded Multilingual Pipeline for AI-Generated Sleep Stories
Generative audio systems can produce large libraries of personalized bedtime content, but ordinary media objectives (retention, completion, and novelty) are poorly aligned with the goal of…The psychophysics of affect in large language models
Good decisions often require considering how outcomes will feel.Can Personal Requirements Become Supervision for Planning?
Managing multiple chronic conditions through diet requires satisfying disease- and medication-specific requirements jointly across meals and days while preserving established eating habits.Steering Vectors as a Training Signal in LLM Post-Training
Steering vectors (SVs) are residual-stream directions that shift the behavior of LLMs when added to hidden states at inference time.STAR: Steering Action Representations during Inference
Vision-language-action models (VLAs) map language instructions and visual observations to robot actions, showing strong capabilities across robotic manipulation tasks.Towards Understanding Score-Seeking in LLMs
Production large language models sometimes reward-hack, exploiting flaws in how tasks are scored rather than performing the tasks as intended, sometimes in highly sophisticated and adversarial ways.