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Artificial Intelligence
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The newest 5,000 papers, from 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 198
Reasoning Models Can Control Their Chains of Thought When They Tell Themselves To
Chain-of-thought (CoT) controllability, the ability of reasoning models to control properties of their CoT, is consequential for both their usefulness and reliable oversight.Beyond Marginal Influence: Interaction-Aware Memory Selection for LLM Agents
LLM-agent memory selection often uses retrieval rankings based on record relevance or individual influence.Annotrace: A Workbench for Step-Level Annotation of Agent Traces
Every study of why LLM agents fail begins by labelling traces by hand, and every such study builds its own throwaway tool.CoTA++: Understanding the Repeat Curse in dMLLMs from an Information Flow Perspective
Diffusion-based multimodal large language models (dMLLMs) decode by iterative denoising with bidirectional attention, which precludes the standard autoregressive key--value cache.FlashReFocus: Interactive Image Refocusing in Seconds
Single-image refocusing changes the focal plane and depth of field of a photograph after capture.Optimist Deep Research: An Iterative, State-Centric Agent for Autonomous Literature Research
Most retrieval-augmented systems treat literature search as a single retrieval step followed by summarization.Designing for Imperfect Prompts: A Simulation-Based Evaluation of an LLM-Based Enterprise Data Assistant Using Knowledge Graphs
Enterprise data assistants using large language models (LLMs) promise democratized data access in organizations.SimOPD: Relational Knowledge Transfer for On-Policy Distillation
A key challenge in on-policy distillation (OPD) is extracting effective supervision from teacher knowledge.MobileInject: Evaluating Reasoning-to-Action Security of MLLM-Based Mobile Agents under Cross-Modal Consistency Injection
Multimodal large language model (MLLM)-based mobile agents are rapidly evolving from conversational assistants into autonomous systems that perceive, reason over, and act on smartphone environments.Self-Reflective Chain-of-Thought (SRCoT): Evidence-Based Text Generation via a Closed-Loop Retrieve--Reflect--Revise Pipeline on Edge LLMs
Large language models (LLMs) can generate fluent outputs that lack source support or conflict with local operational constraints.From Memory Hits to Answerable Evidence: Query-Conditioned Memory Compilation for Long-Term Agent Memory
Long-term agent memory requires recovering answer-relevant evidence dispersed across turns and sessions.AgentOnto: Ontology-Guided LLM Agents for Enterprise Data Analytics
Enterprise data analysis requires agents to connect analytical requests with knowledge distributed across databases, business documents, and existing example tasks.Robust Function Calling for LLM Agents Under Interface Drift
Tool-augmented language-model agents rely on interface text: tool descriptions, argument schemas, and the candidate tool list shown at inference time.Language Models Learn to Improve Language Models
Large language models (LLMs) are increasingly used to automate AI research, including language-model (LM) development, offering a potential path toward recursive self-improvement.OliO: ODE-based Linear Transition Operator for Self-Supervised Time Series Forecasting
Self-supervised representation learning has advanced time series forecasting by capturing robust features from unlabeled data.Monitor-Validity Failures: LLM Safety Evidence Paths at Evolving Framework Boundaries
Modern LLM applications rely on runtime monitors that inspect tool calls, traces, streams, detector outputs, and verifier inputs.AWAM: Active Trajectory-Conditioned View Imagination for Robust Robot Manipulation
Rapid progress in embodied intelligence has enabled increasingly capable robots to follow language instructions and manipulate diverse objects.Generative Policy Improvement from Observational Data
We study how to improve decision policies from observational data to generate better actions when actions are complex, structured objects, such as text messages or images.ScoutRoute: Efficient Mixture-of-Experts Routing Using Internal Language Model Signals
Efficient expert routing is a fundamental challenge in Mixture-of-Experts (MoE) systems, particularly for heterogeneous collections of independently trained Large Language Mod els (LLMs).RECREG: Recovery-based Shielding for Regular Safety Properties in Reinforcement Learning
In many real-world scenarios we need to consider formal requirements, such as safety and constraint compliance, to deploy Reinforcement Learning (RL) agents.