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.
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Newest papers, page 40
We Ran a Research Sprint With AI. The AI Worked. The Research Didn't
Generative AI tools for research are widely deployed, yet individual productivity gains do not guarantee better team research.Balancing Chain-of-Thought and Answer Supervision for Small Language Models on Medical Question Answering
Small language models (<=9B parameters) can support local medical question answering (QA) while reducing privacy and latency concerns, but effective fine-tuning remains challenging.P$^2$-MOPD: Accelerating Multi-Teacher On-Policy Distillation via Parameter Priors
Multi-teacher on-policy distillation consolidates expert capabilities by supervising student-generated trajectories, whereas task arithmetic offers a training-free alternative through linear…ProteoCraft: Protein Design as Proposal-Verification Search
Protein-protein interactions underpin nearly all biological processes.Stacking-Based Weighting for Large Language Bayes in M-Open Settings
Large Language Bayes (LLB) transforms a natural language problem description into a collection of candidate probabilistic programs and performs inference within each model, combining their…Must AI Spell It Out? Pragmatic Comprehension of Alerts in a Time-Critical Task
Assistive systems typically tell users everything, often spending time and attention on what a user already knows, leaving less for what happens next.Measuring Model-Specific Alignment Drift in LLM-Based Opinion Dynamics
Large language model (LLM) agents are increasingly used as synthetic participants in opinion-dynamics experiments, often assuming that an agent's behaviour is fully determined by its prompt.SLATE: A Large-Scale Benchmark for Long-Horizon API Selection in E-commerce Tool Use
Enterprises increasingly want LLM agents to automate standard operating procedures over their software stacks -- mapping each step of a procedure to the right call among thousands of internal APIs…A Guideline-Grounded Multi-Agent Framework for Personalized Exercise Prescription from Clinical and Wearable Data
Translating population-level exercise guidance into individualized prescriptions requires integrating clinical and wearable data, including diagnoses, medications, functional limitations, and…Thinking Fast, Trading Late: System One Decision Models vs the Market
Large language models (LLMs) read company news at scale, and backtests suggest that their readings predict stock returns.FlagRot: Selective Rotation for Low-Bit KV Caches
Long-context inference is bound by the KV cache, which 2-bit codes could shrink about sixfold if their error stays in check.Whose startup does the AI back? An algorithm audit of reputation and demographic signals in LLM-assisted crowdfunding
Large language model (LLM) assistants increasingly advise backers on which crowdfunding campaigns to support.When Music Needs Meaning: Semantic Communication as a Transformative Enabler for the Musical Metaverse
The Musical Metaverse (MM) enables geographically distributed musicians, audiences, sound engineers, and AI agents to interact through synchronized audio, visual, kinematic, and haptic streams…Measure Before You Repair: An Explainable Agent for Blind Restoration of Multi-Artifact 3-D MRI
A brain MRI scan can carry an unknown mix of artifacts, so restoration has to be blind, yet most deep-learning methods are built to correct one known artifact.WASP-Mem: Let Agent Organize Procedural Memory. Human Spend Effort on Diagnosis
LLM agents struggle to automate complex enterprise procedures because static, pre-built harness cannot capture proprietary policies, undocumented behaviors, or state-dependent recovery paths that…Characterizing Adversarial GEO via Implicit Brand Injection
Generative search engines increasingly shape how users discover products, services, and commercial entities by generating answers from retrieved web content.Controlling Action-Head Co-Adaptation to VLM Representation Anisotropy
Modern learning systems increasingly combine pretrained models with downstream heads.A Practical Causal Framework for Autonomous Mobile Robots: From Simulation to Real-World Human Environments
Causal inference has emerged as a powerful paradigm enabling robots to make safe, efficient decisions by reasoning about the ``why'' behind events.ROCm InferaSim: Cut LLM Serving Trial Costs and Deploy the Best Configuration
Serving an LLM efficiently depends on the engine, how the model is split across GPUs, precision, scheduler settings, speculative decoding, KV-cache management, and prefill-decode disaggregation.Recursa: Toward Recursively Self-Improving Foundation Model Systems
Foundation models in changing environments can encounter unfamiliar domain knowledge that their original training did not cover.