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 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 217
First Passage Attention
Augmenting softmax attention with forget gates typically relies on summing decay contributions along the key--query path.ARBOR: Locating Reasoning Failures in Long Chains of Thought through Reasoning State Tracking
Large reasoning models solve complex problems through long chains of thought, in which prior work has documented failure modes such as overthinking, underthinking, and unsupported deductions.LEMON: Equivariant Learning over Attention Maps for Zero-Shot Misbehavior Monitoring on New LLMs
Large language models exhibit misbehaviors that hinder deployment in high-stakes settings.OrderFlowDiT: Transport-Regularized Diffusion Transformer for Probabilistic Limit-Order Supply Forecasting
We study the conditional distribution of limit-order volume submitted over the next five minutes, given the current order book and recent order flow.Graph Serializations for Reasoning LLMs: A Study Across Knowledge Extraction and Structural Reasoning
The way a knowledge graph is serialized as text for inclusion into LLM context can substantially affect downstream LLM performance, with prior work reporting tens of percentage points variations…R$^2$Orch: Recursive Self-Improvement for Agent Orchestration via Self-Play within a Skill-Internalization Loop
In recent years, agentic orchestration has been widely applied to solve complex human tasks.IWOO: Wave Optics Optimizer Improved with Hybrid Strategies for Numerical Optimization and Engineering Applications
The Wave Optics Optimizer (WOO) incorporates optical diffraction and interference into numerical optimization and has shown competitive performance in benchmarks and engineering applications.Agentic Interpretation: Harness-Governed Evidence Construction for Software Agents
Software agents answer behavioral questions about code, such as whether a patch passes tests or which lines caused a failure.spora: A Unified Multimodal Dataset and Platform for Spatial Proteomics
Spatial proteomics (SP) captures the molecular composition and spatial organization of tissues at single-cell resolution, opening a direct view of the cellular ecosystems that drive disease.PACE: Pareto-Adaptive Compression for Efficient Native MLLMs
Native multimodal large language models (native MLLMs) jointly encode visual and linguistic sequences within a unified autoregressive Transformer, emerging as a promising paradigm for multimodal…What Social Media Teaches Us About Accumulative AI Risks
Prominent AI safety discussions emphasize existential threats and catastrophic events, such as AI-enabled nuclear conflict or engineered biological outbreaks.Beyond Explicit Intent: Discovering and Shaping Artistic Intent through Human-AI Co-Creation
Generative AI is becoming an important medium for artistic creation, yet existing interactions often assume that creators can specify intentions in advance and accurately communicate them through…TWIN-MoE: Two-stage Intra-Expert Imputation Network for Incomplete Multimodal Learning
Recent Mixture-of-Experts (MoE) approaches address missing modalities either by routing each missingness pattern to a dedicated expert, which scales poorly as the number of modalities grows, or by…Disentangling Depression from Cognitive Decline in Elderly Speech Using Concurrent Clinical Assessments
Detecting depression from speech in elderly patients with mild cognitive impairment (MCI) is complicated by overlapping acoustic effects of cognitive decline.PW-Pruning: Phase-Aware Expert Selection for Speech-Centric Omni-Modal Models
Sparse routing reduces per-token computation but leaves the full expert bank resident in memory.Why Alternation Speeds Up Counterfactual Regret Minimization?
Solving imperfect-information games at scale rests on counterfactual regret minimization with the regret matching$^{+}$ (RM$^{+}$) update, and a seemingly minor implementation choice accounts for…Generalization Analysis of Biased Stochastic Gradient Methods for Minimax Problems
Minimax optimization refers to a class of optimization problems with some variables to minimize and other variables to maximize.LLM-jp-4 Technical Report
This paper presents LLM-jp-4, a family of Japanese sovereign large language models (LLMs) developed with an emphasis on transparency, reproducibility, and practical usability.Can We Believe AI Peer Review?
As large language models become widely used in scientific review and manuscript revision, AI scores are increasingly serving as feedback for assessing paper quality and guiding edits.Why Do Agent Teams Fail Across Boundaries? A Failure Taxonomy for Agent-to-Agent Systems with Private States
Agents are increasingly interacting with other agents that act for different principals (people or organizations on whose behalf they work), such as a buyer's personal agent negotiating with an…