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 250
MP-MNCA: Morphology-Prior Masked Neighbor Cross-Attention for Efficient Spatial Domain Identification
Spatial transcriptomics jointly captures molecular state, tissue morphology, and spatial organization, yet spatial-domain methods are typically compared only at late training checkpoints, obscuring…SafeDSE: Joint Exploration of Safety Architecture Patterns, Mapping, and Scheduling for Dataflow Applications With Safety Arguments (Extended Version)
Embedded platforms increasingly host safety-related streaming functions next to less critical ones.OneShot: Label-Efficient Detector Weighting for Time Series Anomaly Detection
Time series (TS) anomaly detection (AD) lacks a universal detector, with the best choice determined by the series rather than by the algorithm.Look Back to Move Forward: Learning to Revisit for Agentic Compositional Image Generation
Text-to-image models have made remarkable progress in visual fidelity and instruction following, yet complex compositional generation remains challenging.Learning to GUIDE the Group: Self-Learning LLM Facilitation Across Multi-Party Tasks
As large language models are increasingly adopted as multi-party communication facilitators, there is a growing demand for agents capable of balancing diverse group dynamics across contexts.AutoNovo: Agentic Program Search Discovers Transferable Nucleic Acid Design Algorithms
In-silico optimization of nucleic acids relies on predictive oracles that imperfectly capture biological function, so sequences optimized against one model may exploit model-specific artifacts and…Reflected Proximal Dynamics for Accelerated High-Accuracy Log-Concave Sampling
We study sampling from $π(x)\propto\mathrm{e}^{-V(x)}$ on $\mathbb{R}^d$, where $V$ is $α$-strongly convex and $β$-smooth with condition number $κ=β/α$.Avoiding What Your Teacher Already Knows: Entity Familiarity for Deep-Search Distillation
Deep-search agents are commonly trained by distilling tool-use trajectories from stronger teacher models.ScreenASR-Bench: A Tiered Benchmark for Speech Recognition with Visual Context
Current ASR models perform well on general benchmarks but still struggle with acoustically ambiguous words.Hardware-Friendly Token-Group Activation Quantization for Low-Bit Mamba Super-Resolution
Mamba-based super-resolution models are efficient alternatives to Transformer-based restoration backbones, but their low-bit post-training quantization remains challenging because selective scan…A Survey of Flow Matching in Reinforcement Learning
Flow Matching (FM) has recently emerged as a principled and efficient generative modeling framework for reinforcement learning (RL), enabling expressive, multimodal policy parameterizations via…agent-risk: Risk Assessment for Changes to AI Agents
Before changing a deployed AI agent (a stricter safety gate, a new model), organizations must approve the change, starting from existing logs.REVEAL: Reverse Engineering Agentic Latents from Frontier-Model Traces
Frontier LLM agents perform complex interactive tasks, but their inference costs motivate transferring their experience to smaller open-source agents.SLDBench v2: Active Scaling Law Discovery
Scaling laws predict large-model performance from small experiments, but finding a reliable law itself requires costly experiments.Memory-Efficient Integer-Only Training of Deep Neural Networks
Training neural networks in reduced precision can yield significant efficiency gains, yet all existing methods that scale to standard computer vision benchmarks retain floating-point in at least one…FON: A Draft-Revise Dual-Organ Language Model without Sequence-Level Quadratic Attention
Self-attention assigns two functions to one mechanism-where to read and how to mix-at the price of O(L^2) training, an O(T) decode state, and position signals bound to the training length.Narrative Paradoxes in LLM Inference: Shaping Reasoning Trajectories toward Misalignment
Explicit reasoning in large language models (LLMs) is often associated with reliability, yet it can still pose risks when a model infers harmful goals under a benign context.ReTAC: Residual Test-Time Agentic Computation for Video Spatial Reasoning
Test-time agentic computation can improve multimodal large language models (MLLMs) through planning, tool use, iterative perception, and reflection, but indiscriminate computation may duplicate…HyWe: Unifying Search and Operation for Real-World Hybrid Web Tasks
Real-world hybrid web tasks need both information gathering and page interaction, yet search-based and operation-based agents are developed and evaluated separately.BehaviorFormer: Discovering Behavioral Patterns via Clusterable Next-Token Prediction
Discovering behavioral patterns in open-ended games is challenging due to the lack of clear objectives or ground-truth annotations.