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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 157
Towards Realistic Models of Change: A Causal Perspective on Decision-Making and Dynamical Systems
While statistical learning has made remarkable progress in recent decades, driven by large datasets and data-driven protocols that have transformed scientific practice, it still faces a key…Combining Long-Term Memory and LLMs Comes at a High Cost: From Prompt Injection to Persistent Compromise
The widespread adoption of generative artificial intelligence in recent years has brought a parallel rise in prompt injection and jailbreak attacks.Forging More Tasks into Better Harnesses: Agentic Harness Evolution via Successive Scale Racing
Agentic harness evolution optimizes an agent's instructions, tools, and control flow by using its task execution experiences as evolving evidence.Brittle by Design? Multi-Scenario Reinforcement Learning for Robust Mission Coordination in Systems of Systems
As systems engineering (SE) shifts from monolithic systems to Systems of Systems, Mission Engineering (ME) has emerged as a new line of thinking in SE.Decision language models as affordable and rapid alternatives to LLM judges of clinical generative AI
Automated judges of clinical artificial intelligence (AI) outputs are necessary, but large language model (LLM) judges are costly and slow at scale.Where Should a Stuck Agent Spend Its Next Tokens? Causal Attribution of Inference-Time Resources
Inference-time scaling is often treated as a token-budget problem, but a failed coding agent can seek qualitatively different resources: computation, information, or feedback.Sketch2Sim: an end-to-end modular framework for hand-drawn circuit analysis
This study proposes a sketch-to-simulation system to solve handwritten circuit diagrams.How to Use Parallel Data for Multilingual Pretraining
High-quality human-translated parallel corpora can improve cross-lingual transfer, but are typically too small for large-scale pretraining.When Do Gaussian Priors Fail? A Latent Geometry Investigation of RL Fine-Tuning
Latent diffusion models almost universally place a Gaussian prior on the VAE latent space.Speedrunning Relational Foundation Model Pretraining
Progress on foundation model pretraining is gated by who can afford a trial, and relational pretraining is no exception.DualHeads: Reward-tilted few-step diffusion made simple
Distilled diffusion models generate high-quality images in a few sampling steps, but aligning them with task requirements and human preferences is difficult.Agent AI Zarządzający Siecią Open RAN Zorientowana na Użytkownika
Jednym z najważniejszych wyzwań związanych z implementacją sieci Open RAN o architekturze zorientowanej na użytkownika jest odpowiednie formowanie tzw. klastrów obsługujących.A General Topological Symmetry Index for Critical Orbits In Neural Network Loss Landscapes
A systematic understanding of the global structure of neural-network loss landscapes remains challenging due to their high dimensionality.To Manipulate or Not: Opinion Dynamics in LLM Interactions
Large language models increasingly take part in extended conversations where they can both shape and be shaped by another party's views, yet most persuasion research measures only one side of that…inr2action: Encoding Robot Episodes as Neural Implicit Representations for Recall and Action
Long-horizon robotic operation requires memory that scales with essential information rather than execution time.RL-IF: Tracking Non-local Training Data Influence for Online Reinforcement Learning
Online reinforcement learning (RL) has achieved significant success in decision-making tasks, but modern online RL remains highly sensitive to the quality of training experience.SANE: Automated Scorer-Specific Metamorphic Testing for LLM Judges
LLM judges increasingly mediate benchmark evaluation, model selection, data curation, and training.Fig: Automated Multiagent Behavior Elicitor
Many social evaluations for multiagent systems study behaviors as they emerge from environments instead of systematically intervening in the environment to elicit such behaviors.Hidden Messages Between Diffusion Language Model Agents: Causal Evidence for Latent Communication
Diffusion language models form answers through a sequence of revisable continuous states, but multi-agent systems usually discard those states and make agents communicate only after decoding text.JaxMARL-BC: Multi-Agent Reinforcement Learning for Macroeconomic Modelling, in Seconds
Multi-agent reinforcement learning (MARL) offers a principled way of populating simulated economies with many heterogeneous decision makers.