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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 96
Arya Forge: Auditing Validation and Release Approval for Financial Instruction Data
Financial instruction-data pipelines must distinguish content validity from permission to release a particular dataset.Uncovering the Turing Test's Latent Signal: Indistinguishability as a Reward
Can a model learn by trying to fool another model?ToDoPro: Faster and Better Reference-Based Generation: Early Token Reduction via Downsampled Self-Probing
Recent generic reference-based image generation models natively support multiple conditions by concatenating all reference image and text tokens into a joint sequence processed by a single Diffusion…Centralized Critics for N-Agent Ad Hoc Teamwork
Centralized training with decentralized execution (CTDE) has become the dominant paradigm in multi-agent reinforcement learning (MARL), motivating extensive study of what privileged information…Precedence-Aware Resource Allocation: Extending the AUTOC Framework to Multi-Level Treatments
Many real-world decision problems require allocating limited resources across individuals to maximize total benefit often through interventions that vary in intensity rather than binary treat-or-not…Silent and Costly: Characterizing and Detecting Prompt-Caching Mis-Integration in LLM Agents
Large language model (LLM) services process massive volumes of user requests, resulting in substantial inference costs.SPARTA: A Sparse Ternary LLM Accelerator with Adaptive Attention and Unified Datapath for Long-Context Edge Inference
LLMs on edge devices are constrained by limited memory and bandwidth.TrustJev: Separating Policy Authority from Untrusted Evidence in LLM-Based Decisions
Decision models enable software to select from predefined actions using natural language inputs.Logic Hijacking of RAG: Single-Document Poisoning via Local Optimization
Single-document corpus poisoning under black-box access poses a severe threat to Retrieval-Augmented Generation (RAG).Streaming Recurrent Memory
Natural intelligence learns from a continuous stream of sensorimotor experience: data can arrive at high bandwidth, and behavior adapts to feedback as soon as it arrives, even when it is delayed.Collective Emergent Alignment: Measuring and Amplifying Interaction-Induced Reasoning Alignment in Multi-Agent LLMs
Multi-agent large language model (LLM) systems can exhibit emergent behaviors through interaction, yet whether a similar phenomenon exists for reasoning alignment remains largely unexplored.Beyond Behaviour: A Stimulus-Response Safety Evaluation of Vision-Language-Action Models
Humans exhibit biological sensitivity to safety-critical stimuli that can trigger defensive action.Recovering Black-Box Point Cloud Models from Pose Shifts via Derivative-Free Optimization
Point cloud models are increasingly deployed through score-only black-box interfaces.DecoyCount: Evaluating Visual-Reasoning Misalignment in Counting
Visual counting benchmarks report whether vision-language models produce the correct number, but not whether errors arise from perception or reasoning.UniGFM-RAG: Unify Graph Foundation Models and Large Language Models for End-to-End Retrieval and Reasoning
Large Language Models (LLMs) have shown remarkable capabilities across tasks, but they still struggle with complex reasoning that requires integrating scattered knowledge.GADAR: Generalizing Across Domains via Action Ranking for Classical Planning
Learned policies for classical planning act without search, but each is tied to the domain it was trained on: network modules per action schema, parameters per predicate, or vocabulary-sized…DocTalk: Enhancing Medical Knowledge Retrieval via Fine-tuned Large Language Models with Chain-of-Thought Reasoning for Robust Clinical Decision Support
The rapid advancement of large language models (LLMs) in healthcare has opened new possibilities for AI-assisted clinical decision-making; however, safe and effective deployment remains challenging…Adaptive Retrieval, Selective Answers: Evaluating Conformal Factuality in Agentic RAG
Retrieval-augmented generation (RAG) can improve factual grounding without guaranteeing that every generated claim is supported.CoDeRNet: Selective Cross-Task Routing under Heterogeneous Supervision for Change Detection and Captioning
Change Detection & Captioning (CDC) aims to jointly localize changed regions and describe their semantic content from bi-temporal remote sensing images.ClinVerse: A Realistic Multi-Agent Diagnostic Environment for Training and Evaluating Medical Agents
Disease diagnosis is a key application of large language model (LLM) agents in healthcare.