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.
Get the few papers worth your time in Artificial Intelligence every morning.
Follow Artificial Intelligence and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 191
Agents' Last Doubt: Knowing When to Act and When to Step Back in Tool-Using Agents
Tool-using LLM agents repeatedly face decision points under uncertainty, choosing between autonomous action, additional information gathering, and human escalation.Towards an Intelligent Decision Engine for Smart Contract Deployment
Layer 2 (L2) blockchain solutions emerged in recent years, predominantly in the Ethereum ecosystem, as a viable option for scaling a main blockchain network (L1).Distillation, Self-Training, and the Fragility of Learned Chemical Reasoning
Automating synthesis planning for small-molecule drug design requires chemical reasoners that are accurate as well as open to inspection and adaptation, yet frontier language models remain…SWE-Bench Pro V2: A Cleaner, Harder-to-Game Coding Benchmark
SWE-Bench Pro is a widely used benchmark of long-horizon software engineering tasks for coding agents.Landmark-Free and Scale-Blind Multi-View Registration of Preoperative Liver Models to Intraoperative Surfaces
Augmented-reality guidance in laparoscopic liver resection requires aligning preoperative 3D liver models from CT/MRI with intraoperative surfaces.Training-Free Prompt Selection for Efficient Reinforcement Learning With Partial Rollouts
Reinforcement learning with verifiable rewards (RLVR) has emerged as a prominent paradigm for training reasoning models, but its computational cost makes efficient data selection increasingly…LoopHIL: Looping Hardware into LLM-assisted Agents for Wireless Embedded Systems
LLM agents are widely used for software development and debugging, but their adoption in embedded systems, especially for wireless tasks, remains limited.Analyzing Repetition and Interference Effects in Memory-Constrained User Simulators
User simulators can help evaluate and train AI systems to interact with humans at scale.Who Plans, Who Edits? Verified, Cost-Aware Division of Labor for LLM-Driven Analog Layout Repair
Language-model agents can repair analog layouts when sign-off tools check every edit, but which model should plan a repair, which should edit it, and at what cost remain open questions.Encoder-Free Multimodal LLMs Learn Implicit Encoders
We empirically analyze two recently proposed encoder-free multimodal LLMs, Gemma-4 12B and Inkling-Small.Towards Reinforcement Learning for Space Robotics: Fast Training and Reliable Real-World Transfer
This work demonstrates the use of a fast simulation-based training framework to learn control policies using reinforcement learning.Probing Ambiguity: Adversarial Intent Resolution for Robust Text-to-SQL
Text-to-SQL systems typically assume a one-to-one mapping between natural-language queries and correct SQL translations.Cortex: A Fixed-Point Theory of Governed Coding Agents - Technical Report
A coding agent combines a large language model (LLM) with a harness that plans, edits, and executes code.AM-Bench: A Unified Taxonomy and Evaluation Suite for Agentic Misalignment
As LLM-based agents are deployed with increasing autonomy in real-world environments, a critical failure mode emerges: agentic misalignment, where agents choose harmful actions over failure.Can Compact Open-Weight Large Language Models Recover Mobility Events from Incomplete Trajectories? A Controlled Evaluation Using Air Trips
Incomplete mobility trajectories can obscure the observations needed to identify important travel events and their endpoints.From SEC Filings to Financial Signals: Evaluating LLMs on Stock Market Reactions and Analyst Forecasts
Form 10-Q MD&A sections combine long-form management narrative with accounting and forward-looking information.SPIDES: Information-Flow Control for Browser Agents
Browser agents automate complex workflows by reading and acting on arbitrary page content, but this flexibility exposes them to prompt injection attacks and unintended data exfiltration.SteerSearch: Interactive Search Reasoning with Mid-Response Steering
Search-augmented language models increasingly serve as long-horizon research agents, yet most open training methods assume a fixed user goal throughout search.Unbounded Losses, Unchecked Inputs: Measuring the Safeguards of LLM Options-Trading Agents
Large language model (LLM) agents now place options orders at retail brokers, and developers publish open-source options agents faster than anyone has examined them.Not Every User Says It All: Training Tool-Using Agents Beyond Ideal Simulated Users
Tool-using agents are trained and evaluated almost exclusively with strong simulated users who state every detail clearly, yet real users are often weaker.