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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Trail: Accurate Local Smart Home Control Using Decision Models
Natural-language driven smart home control remains challenging: cloud-hosted Large Language Models (LLMs) raise privacy concerns, while local Small Language Models (SLMs) can generate invalid…Learning from an Imitable Teacher: Competition Solution for the MetaFine Challenge
The MetaFine Open Competition (RoboFineMani workshop, CoRL 2026) evaluates fine-grained manipulation beyond binary success.LM6-CastBench: A Geometry-Aware Simulation Dataset for Transient Thermal Prediction in LM6 Sand Casting
Transient thermal fields during solidification connect casting process conditions and cooling behaviour to the formation of defect-prone regions in aluminum cast ings.Discovering Models for Experimental Quantum Systems with Agentic AI
A central obstacle in realizing color center cavity-QED-based quantum technologies is inhomogeneity, or disorder, among individual emitters.Log-Driven Semantic Tuning for Mixed Integer Programming Solvers
Automated configuration of mixed-integer programming (MIP) solvers largely relies on black-box optimization.XLA from the Trenches: Correctness on TPU Workloads at Scale
Accelerating modern foundational models has pushed domain-specific compilers toward increasingly complex, multi-tiered optimization pipelines.Autonomous Analysis of Thermoelectric Materials Big Data by Multi-Agentic AI and Construction of a Knowledge Base and Specialized AI
Extracting knowledge from large databases of experimental materials data requires repeated analyses and reusable records of their choices and results.TopoQuant: Topological Framework to Characterize Behavioral Shifts in Quantized Large Language Models
Post-training quantization (PTQ) reduces the com putational cost of large language models (LLMs), but it can introduce internal structural and behavioral changes that are not captured by traditional…Evidence-grounded large language models guide perovskite solar cell design and optimization
Using large language models to interpret experimental evidence, design discriminating experiments and formulate well-supported mechanistic explanations remains a central challenge in materials…Selecting LLM-Generated Hypotheses Raises Truth Beyond What an LLM Panel Expects: A Pre-registered Study on NAS-Bench-201 and HPOBench
LLM research-ideation systems aim for hypotheses that are both true and non-obvious, yet neither property can normally be checked.FastAgent: A Physics-Aware FastFluent-to-Fluent Workflow for Rapid CFD Screening and Industrial Steam Dewaxing Design
Industrial computational fluid dynamics (CFD) becomes costly when complex geometries, long transients and coupled physics must be evaluated across large design spaces.Designing Behavioral Profiles for Language Model Simulation of Out-of-Distribution Human Behavior
Large language models (LLMs) are increasingly used to simulate human behavior, but which descriptions of people improve prediction when experimental designs change remains unclear.Precedent Labels and Facts Shift LLM Approval Decisions in Opposite Directions
When a language model decides refund or claim requests under written policies, the system can show it similar past cases.Getting a Grip: Operating Human-Agent Software Teams Through Governed Messages
Software is increasingly developed by teams in which several people direct many coding agents from different vendors.SAVIER: Source-Anchored Visual Inspection and Evidence-Guided Repair for Vietnamese Cultural Text-to-Image Generation
We present SAVIER, a training-free, one-pass framework that repairs the depiction of a named Vietnamese cultural entity in a generated image while preserving the scene details requested by the user.Architecting Fairness-Aware LLM Interactions
Large Language Models (LLMs) are increasingly used as decision-support tools but may generate stereotypical, discriminatory, or unfair responses.Can Jev Improve Demonstration Retrieval for In-Context Learning?
Demonstration selection plays a crucial role in the effectiveness of in-context learning (ICL) for large language models (LLMs).Beyond Synthesis Conditions: Linking In-situ Growth Dynamics to Carbon Nanotube Forest Properties through Multimodal Machine Learning
Machine learning for chemical vapor deposition (CVD) of carbon nanotubes (CNTs) has largely mapped static synthesis conditions to final properties, implicitly treating these conditions as a complete…ResMamba: A Dual-Path Convolution-Mamba Model for Music Genre Classification
Music genre classification remains a fundamental yet challenging task in music information retrieval, requiring models that capture local time--frequency patterns and long-range temporal dependencies.Inherited or Learned? Backdoor Selectivity in Distilled Language Models
Distillation is a routine step in building small language models, and a backdoored teacher can pass its backdoor to the student.