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.
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Newest papers, page 93
FilingLoop: Evaluating and Evolving LLM Agents for Corporate Disclosure Review and Revision
Public disclosure repositories such as SEC EDGAR support informed investment through web access to corporate filings.Beyond Low-Pass Dynamics: Frequency-Selective Spiking Reservoirs with Resonant Neurons
Spiking reservoir computing combines the training efficiency of fixed recurrent reservoirs with the energy efficiency of event-driven inference, where computation is triggered by sparse spikes…TERRA: Task-Oriented Edge AI for Regional Fire Detection with Identity-Free Reporting
Distributed fire-monitoring systems may involve many sensing devices reporting over a shared uplink, even though the operational objective is often to identify regions exhibiting evidence of fire…What Actually Matters? A Paired Evaluation of Inference Settings for $π_{0.5}$ on BEHAVIOR-1K
Vision-Language-Action (VLA) models offer a promising paradigm for general-purpose household robotics.SciGame: Let Agents Play the Scientific Discovery Games in the Real and Counterfactual World
Large language model agents are increasingly used for scientific discovery.VerifiedLab: Harnessing Knowns for Unknowns
Across human history, knowledge has undergone several transitions, from orality to writing and then to digital archives.GARDEN: Generalist Autonomous Reward Design Through Evidence Navigation for Cooperative Multi-Agent Reinforcement Learning
Cooperative multi-agent reinforcement learning (MARL) enables teams of agents, such as robots and autonomous vehicles, to learn coordinated behavior, but what such teams learn is largely determined…Understanding Large Language Models as Numerical Optimizers
Large language models (LLMs) have emerged as potential tools for numerical optimization.NLP-based Message Prioritisation for Opportunistic Routing: A Case Study of Nepal Earthquake Emergency Communication
This dissertation investigates whether Natural Language Processing (NLP) based semantic message prioritisation can improve the treatment of urgent disaster messages in opportunistic emergency…SkillMem: Compact External Skill Memory for Latent Multi-Agent Reasoning
Latent multi-agent systems reduce inference cost by keeping intermediate reasoning and inter-agent communication in continuous representations.\ Reusable skills, however, are commonly supplied as…SAG-Sep: Sparse Augmented Graphs and Onion-Guided Search for Rounded Capacity Cut Separation
Rounded capacity cuts (RCCs) are among the most effective cuts for capacitated vehicle-routing relaxations, but exact separation is computationally prohibitive at scale.Statistical Detection of Positional Bias in LLM-Based Recommender Systems: Methodologies and Empirical Evidence
Large Language Models (LLMs) are increasingly used as recommendation generators in conversational recommender systems (RS) via retrieval-augmented generation (RAG).Self-Supervised Latent Action-Conditioned World Modeling for Time Series
Time-series data play an important role in various tasks, such as weather forecasting, web traffic analysis, and speech recognition.Merge and Branch: Efficient Tree-Structured Supervised Fine-Tuning of LLMs for Recommendation
LLM-based generative recommendation reads long, text-rich interaction histories but generates only short semantic identifiers (SIDs).GAUSS: A Workload-Aware Analytical and Monte-Carlo Simulator for LLM Inference Serving
Large language model (LLM) inference has become an operational workload that fleets must provision, monitor, and bill against latency service-level objectives (SLOs).Towards Generalizing Pretrained All-Atom Representations to Unified Binder Design
PairFormer-based all-atom models demonstrate strong capabilities in biomolecular binder design.Are Seismic Foundation Models More Than Glorified Feature Extractors?
Earthquake sequences are stochastic on two separated timescales: the seismic waves of any individual earthquake propagate over seconds to minutes, while the earthquakes themselves arrive as a…"It Would Make a Geordie Feel at Home": Regional Accent Perceptions and Speech Accommodation in Voice AI
Automatic speech recognition (ASR) systems often perform less accurately for speakers of regional dialects, but less is known about how users respond to these limitations and how regional voices…Algorithmic Bias from the Perspectives of Healthcare Professionals
This paper focuses on algorithmic bias of machine learning and artificial intelligence applications in healthcare information systems.Making Smart Homes Fit for Autistic Children: Family Work and Monitored Independence
General-purpose smart-home technologies are increasingly present in family life, yet how they support or disrupt autistic children and families with autistic children remains underexamined.