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.
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 24
Modelling lock-in of AI adoption through skill erosion
Generative AI can improve immediate performance but may erode the human skills required for future work.FourSight: Stable FP4 RL Post-Training via Sequence Filtering and Sparse Channel Compensation
Reinforcement learning (RL) post-training increasingly targets low-bit deployment, with NVFP4 weight-and activation quantization (W4A4) becoming the state-of-the-practice format.Fault-tolerant shallow recurrent decoders for sparse sensing with missing sensor measurements
Real-world sensing systems are inherently imperfect: sensors may fail, intermittently disconnect, operate with asynchronous sampling rates, and be subject to noise, leading to measurement streams…VisSearch-Bench: Evaluating Long Horizon Visual Search in Multimodal Agents
Multimodal agents use web and image tools to answer questions beyond their internal knowledge.Artifact-to-Capability: Diagnosing Breaks in Capability Formation of Self-Evolving Agents in a Controlled Environment
Self-evolving agents write interaction experience into artifacts and reuse them in later tasks.Shuffled OPSD: When Semantic Consistency Hurts On-Policy Self-Distillation?
Knowledge distillation improves a student model's reasoning ability through supervision from a teacher.Who is the Pronoun Pro? Comparing LLMs and Humans at Number-Disambiguation of 'they'
This study evaluates whether large language models (LLMs) can reliably replace or complement human research assistants in linguistically complex annotation.LLMs as MDP Designers: A Dependency-Aware Agentic Framework for Automated Robot Policy Generation
We investigate the automated generation of executable robot reinforcement learning (RL) policies from natural-language task descriptions.GeoFaham: Domain-Specialized Multi-Agent Geospatial Analytics for Disaster Response
Real-world geospatial decision support requires more than single-step retrieval or code generation.Learned Smartphone ISP on Mobile GPUs: Mobile AI 2026 Challenge Report
With the increasing importance of mobile camera quality in modern smartphones, growing attention has been directed toward computational photography and advanced image signal processing (ISP)…Rethinking GA2Ms: performance and out-of-distribution generalisation
Generalised Additive Models (GAMs) are a cornerstone of interpretable machine learning, offering transparent predictions through structured additive decompositions.RGB Photo Enhancement with Deep Learning on Smartphone GPUs: Mobile AI 2026 Challenge Report
On-device RGB photo enhancement is a popular task that is needed for quality improvement of photos captured with mobile devices as well as for retouching of images acquired through other sources.ALBI: LLM-Guided Inductive Logic Programming via Iterative Generate-Test-Constrain Refineme
We introduce ALBI (Agent for Learning By Induction), a neuro-symbolic ILP framework that replaces the ASP-based hypothesis generator in the Learning from Failures (LFF) paradigm with a Large…Do Agentic Policies Need to Look at Every Step? Geometric Abstraction for Reasoning and Action
Recent multimodal language models can reason directly about robot scenes, but it is unclear whether they need to repeatedly reinterpret raw visual observations at every step of an interaction.FloMo: 3D Scene Flow as a World Action Model Intermediate for Learning from Human Video
Pretrained video generation models distill internet-scale motion priors into robot policies, but full video is a redundant signal for action prediction.VIGOR: Visual Gain Ordering for Hallucination Mitigation in Multimodal Discrete Diffusion Language Models
Multimodal discrete diffusion language models (dLLMs) generate responses through iterative mask prediction and offer a promising alternative to autoregressive large vision-language models.Trajectory Evaluation via Rollout-Free World Model for End-to-end Autonomous Driving
Although existing candidate trajectory evaluators have substantially improved end-to-end planning accuracy, their underlying mechanism remains suboptimal.LatentTriad: Pre-Action Risk Representations for Malicious Agent Skill Detection
Large language model agents are increasingly extended with reusable skills, but untrusted skill content can induce operations outside the user's task.The Platonic Brain: Representational Convergence in EEG Foundation Models
The Platonic Representation Hypothesis (PRH) predicts that artificial neural networks converge on shared representations as scale and performance increase.Molecular Prior Networks
Predicting affinity between small molecules and their protein targets remains one of the central problems in drug discovery.