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Artificial Intelligence
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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 134
Rethinking Multi-View Fusion for Urban Representation Learning
Urban region representation learning encodes heterogeneous urban signals, such as mobility flows, points of interest, and land-use patterns, into unified embeddings for downstream tasks, including…SWE-Clar: Can Coding Agents Clarify Incomplete Client Requirements and Deliver Greenfield Software?
Greenfield software development in freelance settings requires coding agents to turn incomplete client requests into working software.Machine-Readable Operator Manuals over the ISO 11783 Network for Offline, Multilingual LLM Assistance
If agricultural machinery is to support intelligent, offline assistance, then the system must access technical documentation dynamically.FSVL: Taxonomic Fast-Slow Vision-to-Language Collaborative Framework for Interpretable Confusable Fish Species Identification and Knowledge Generation in the Middle Yangtze River
The Yangtze River Basin is a critical region for freshwater biodiversity conservation.TACS-RF: Tool-driven Agentic Circuit Synthesis of RF and mmWave Modules
We present the framework of TACS-RF - a Tool-driven Agentic Circuit Synthesis of RF and mmWave modules.Effectiveness of Curriculum Learning Depends on Reward Sparsity and Competing Optima
While animals and people tend to learn a task more quickly and reliably when they first train on simpler versions of it, curriculum learning's effectiveness in artificial settings varies, and…Knowing When to Stop: The Evidence-Action Gap in Coding Agents
Coding agents are trained to complete tasks, and they keep trying even when the environment makes completion impossible.Learning Structured Sparsity for Large Models: Bridging Model Compressibility and Efficient Inference
Scaling laws continue to reward increases in model scale, while the resulting computational and memory demands drive greater reliance on cloud infrastructure for inference.Permission to Retry: A Study of Authorization and Recovery in AI Agent Workflows
A durable agent can resume a consequential action while its authority changes and the action's external outcome remains uncertain.Beyond On-Policy vs. Off-Policy: At What Level Should LLM Agent Distillation Follow the Student?
Distilling interactive LLM agents requires choosing between teacher-generated demonstrations and student-generated experience, corresponding broadly to off-policy and on-policy distillation.ENCL: Enabling Efficient Neuromorphic Continual Learning with Local Learning Rule and Sub-Network Freezing Strategy
Continual learning (CL) in neural networks is a promising learning approach for updating the knowledge of deployed systems based on new data encountered at run time, that have not been learned…$M^3$: A Multi-LLM System for Multi-Turn Jailbreaking as a Markov Decision Process
Modern Large Language Models (LLMs) remain vulnerable to carefully orchestrated multi-turn interactions that progressively bypass safety mechanisms.Kolibri: A Sovereign European Model on the Pareto Frontier
This report introduces Kolibri, an English-German mixture-of-experts transformer with 78.1B total parameters and 3.46B active parameters per token, released as open weights under the Apache 2.0…RobustNCL: Robustifying Neuromorphic Continual Learning under Transient Faults with Lightweight Detect-and-Cure Strategy
In neural networks, continual learning (CL) is a prominent approach for enabling deployed systems to adapt to dynamic operational environments by effectively learning from new unseen data at runtime.A Mathematical Theory of the Jacobian Lens
Recent work from Anthropic introduced a new interpretability tool, called the Jacobian lens (J-lens, Gurnee et al., 2026).Knowing Whom to Trust is not Enough: The Trust--Agreement Gap in Repeated Multi-Party LLM Negotiation
Large language model (LLM) agents increasingly participate in negotiations on behalf of individuals and organizations, yet they remain vulnerable to manipulation, particularly in repeated…Reproducible Evaluation as the Substrate for Safe Prompt Compression in Production Agents
Evaluating conversational agents that act on live, mutable enterprise data is hard: replayed sessions drift as backend state changes, and a benchmark built today can silently go stale as the data it…Agentic AI Defense: Decode-Time Provenance Binding for MCP
Agentic AI systems using the Model Context Protocol (MCP) are vulnerable to indirect prompt injection through untrusted tool outputs.Spectra: Multi-Scale Implicit Decomposition for Deepfake Detection
Deepfakes increasingly undermine trust in digital media, yet existing detectors often struggle to generalize across unseen manipulation techniques, compression levels, and dataset shifts.The Helpful Agent Problem: When Emergent Cooperation Among LLM Agents Bypasses Intended Workflows
LLM agents are increasingly deployed in collaborative settings where they pursue separate tasks while sharing resources and operating under review or oversight processes.