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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 145
LLM2Cert: LLM Synthesis of Certificates with SMT/Lean Verification
Lyapunov functions and barrier certificates give state-space guarantees of stability and safety, but synthesizing and verifying them---especially for nonlinear, high-dimensional systems---remains an…Decision Making and Ride Comfort Evaluation Based on Lane-Change Prediction for Autonomous Vehicles
Predicting surrounding vehicles' lane-change intentions enables autonomous vehicles to anticipate potential hazards and respond proactively rather than relying solely on reactive maneuvers.PLE: Physical-Engineering's Last Exam
Frontier language models now score above 90% on popular knowledge benchmarks and are increasingly deployed as agents that carry out multi-hour professional work.Tradeoff-Aware Territory Design: A Multi-Objective Decision System for Enterprise Customer-to-Seller Allocation
Enterprise customer journeys are shaped not only by product experiences and marketing, but also by recurring resource-allocation decisions.Collaborative In-Context Learning for Indoor Radio Map Estimation
Indoor radio map estimation (RME) is essential for wireless applications such as coverage planning, localization, and network deployment.Before the Ticket: Grounding HPC User Support in Documentation and Resolved Tickets with an Agentic LLM Assistant
Most questions that reach an HPC help desk have already been answered in the center's user guides or in a ticket someone else filed last semester; users still file new tickets because the guides are…RubricCraft: Where Solutions Diverge, Criteria Emerge
Evaluating language agents on open-ended, artifact-producing tasks is difficult: model-based graders can be inconsistent, while exhaustive programmatic checks are often impractical.VLMProbe: An Open-source Library for VLM Probing and Interpretation
Understanding how vision-language models use visual information requires connecting internal representations to model behavior.AGQ: Action-Guided Ultra-Low-Bit Quantization for Vision-Language-Action Models
Vision-language-action (VLA) models enable robots to perform tasks specified through natural-language instructions, but their large weight footprint challenges deployment on memory-constrained…Diagnosing and Mitigating Evidence Misgrounding in Multimodal Knowledge Editing
Multimodal knowledge editing aims to update visually grounded facts in Multimodal Large Language Models (MLLMs) while preserving unrelated text and visual behaviors.Evaluating Visual Language Models on Visual Grounding for Visually Impaired People
Visual grounding (VG) in visual question answering (VQA) is a fundamental capability of Vision-Language Models (VLMs), enabling the detection of the most relevant region in an image to answer the…AnalogPortBench: Benchmarking LLMs on Analog Circuit Porting
Analog circuit design still relies heavily on expert knowledge, and porting proven designs to new process nodes is a recurring bottleneck.KPHarness: Co-Evolving Knowledge and Probing for Long-Horizon Gaming Harnesses
A failed gaming trajectory reveals that an agent needs intervention, but not necessarily how its execution harness should change.The Router Already Knows
Mixture-of-experts (MoE) models already make a sparse choice for every token: which experts should process it.Harness Self-Evolution for Long-Horizon Terminal Agents
Long-horizon terminal agents may solve a task in one run yet fail across repeated runs.MLIPS: Multi-Layer Indexer Pool Sharing
Sparse attention limits the keys used by each query, but finding those keys can still require a full-prefix scan at every layer.Scaling Graph Reasoning in Language Models with Learnable Graph Positional Encodings
Solving reasoning tasks supported on graphs typically requires providing a Language Reasoning Model (LRM) with a serialized description of the graph.Beyond Scalar Leaderboards: Adaptive Sampling for Pareto Frontier Identification in Multi-Objective LLM Arenas
The evaluation of large language models (LLMs) is inherently multi-objective, as different models may offer different tradeoffs across performance dimensions such as math, code, and writing.Ask to Distill: Learning to Synthesize Data for On-Policy Distillation
On-policy distillation (OPD) can succeed with surprisingly few training questions, motivating a view of questions as carriers of distributional knowledge transfer.Recoverability and Verifier Strength: Two Measured Preconditions for Unattended Agent Self-Improvement
Agent platforms are starting to improve their own agents: they read a deployed agent's execution traces, derive a change, have an automated verifier approve it, and release it with no human author.