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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 12 October 2026 to 6 November 2026: 4,992 arXiv preprints and 8 OpenAlex records.
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Newest papers, page 236
LinMorph: Learning to Morph Weights for Efficient Video DiT Linearization
Post-hoc linearization is an attractive way to accelerate pretrained Video Diffusion Transformers (Video DiTs), yet existing methods largely treat the quality loss induced by attention replacement…CineMem: Attention-Aligned Fine-grained Memory Retrieval for Multi-Shot Long Video Generation
Autoregressive video generation relies on memory retrieval to model long-range dependencies.GLST: Global-Local Spatio-Temporal Memory Decomposition Framework for Online Chained-Goal Navigation
Autonomous navigation in real-world environments often requires long-horizon operation under partial observability and evolving goals.Learning How to Remember: Memory Modality Selection for GUI Agents
Recent advances in vision-language models (VLMs) have substantially improved the capabilities of GUI agents, while memory augmentation has emerged as a promising approach for reusing knowledge from…MERIT: Multimodal Evidence Reasoning over Image Tables
Table reasoning with language models typically assumes access to clean textual tables.AI-Enhanced Hyperspectral Imaging for Intraoperative Detection of Low-Grade Glioma: A Clinical Study
Current image-guided neuronavigation techniques, such as intraoperative MRI and ultrasound, are limited by high costs, limited sensitivity and operational complexity.HaloBlock: Faster and Better Decoding for Diffusion Large Language Models
Diffusion large language models (dLLMs) have attracted increasing research attention due to their bidirectional attention and arbitrary order decoding.FETALFusion: Resolution-Aware State-Space Modeling for Multi-Domain Fetal Head Segmentation
Head circumference (HC) measured from 2D ultrasound is a routine marker of fetal growth, and automating it needs segmentations whose boundaries hold up on individual scans, not only on average.Virtual Head Attention
The design of attention mechanisms in long-context large language models faces an ``impossible triangle'' among KV cache size, training and prefill FLOPs, and model quality.Better Capturing Interactions Between Products in~Retail: Revisited Negative Sampling for~Basket Choice Modeling
Brick-and-mortar retailers face many different challenges that involve understanding thoroughly its products catalog and customer preferences.BELT : BEhavior-Aligned Low-Rank KV Cache Compression with Learned Top-k Rank Allocation
Long-context inference makes the key-value (KV) cache a major memory bottleneck for large language models.Seeing Depth but Choosing Cues in Vision-Language Models
Do vision-language models use depth information to judge which object is closer, or rely on image-plane cues?Seeing Through the Forgery Is Not Enough: Regressive Sycophancy under Fabricated Evidence in Medical Vision-Language Models
A medical vision-language model may analyze a given CT scan and correctly detect both kidneys in view.Saliency-Guided Replay for Continual Learning in Deep Spiking Neural Networks
Spiking Neural Networks (SNNs) are promising for energy-efficient neuromorphic computing, but they still suffer from catastrophic forgetting when learning tasks sequentially.Match the Canvas, Not Just the Answer: Predictability-Aware SFT for Diffusion Language Models
Diffusion language models (DLMs) enable flexible parallel generation by resolving tokens according to the model's evolving predictability rather than a fixed left-to-right order.SWEPatchTest: Evaluating Software Tests Beyond Reproduction
Coding agents use generated tests to decide whether a proposed patch satisfies an issue's requirements.Cost-Efficient Privacy Enforcement for Email-Generating LLM Agents under Strategic Information Requests
LLM agents now act as delegated communication intermediaries: they read private context, draft messages, and send externally visible emails on behalf of a user.Correcting or Continuing? What On-Policy Distillation Learns from Student Errors
On-policy distillation (OPD) trains a student on its own rollouts under a frozen teacher, mitigating the distribution mismatch of off-policy supervision.LatentRemedy: Efficient Remedy For Non-Prefix KV Cache Reuse in Multi-Agent Systems
Non-prefix KV cache reuse is a promising approach for improving inference efficiency in multi-agent systems as agents share the same context blocks.SHELDON: Reasoning through Dual Search over Hypothesis and Observation Spaces
Test-time scaling has enabled LLMs to solve increasingly complex reasoning, discovery, and optimization tasks.