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 56
From Evaluation to Evolution: Benchmarking Image Editing and Evolving Image Models
Real-world image editing requires coordinating multiple visual transformations with content preservation and reference constraints, yet aggregate scores can readily obscure unmet local requirements.RTL-Interact: Training EDA-Interactive Models for Multi-Task RTL Design
Large language models offer a promising route to register-transfer-level (RTL) design, but reliable implementations require checking and revision based on electronic design automation (EDA) tools'…Coarse3D: Controllable and Faithful Sparse Structure Generation for Image-to-3D
Coarse-to-fine 3D-native generation relies heavily on the first-stage sparse structure, which determines the global orientation and overall geometry for subsequent refinement.TRIDENT and SHAKTI: A Framework and Benchmark for Hindi AI-Text Detection
As Large Language Models (LLMs) become increasingly multilingual, distinguishing human-written from AI-generated text is essential for maintaining information integrity.Experts Exhibit Structured Redundancy: Structure-Preserving Expert Pruning for Mixture-of-Experts Large Language Models
Sparse MoE mechanism significantly improves the trade-off between model capacity and inference efficiency.MEMIG: Self-evolving Memory Construction for Antibody Optimization
Memory has become central to self-evolving LLM agents, which store and retrieve experience from past rollouts to guide future decisions.Rome Wasn't Built in One Turn: Replay-Grounded Reward Signals for Long-Horizon Freeciv Agents
Training language-model agents to play long-horizon strategy games is hard because deterministic feedback is sparse and often arrives only at the end of a game.From 1D Benchmarks to Complex 3D Geometries: Can Agents Reliably Specify Problems for Automated PDE Simulation?
Turning an engineering request into a simulation requires consistent geometry, physics, boundary conditions, and numerical settings.ANGLER: Verifier-Grounded Benchmarking with an Adaptive Attacker for Web Agents
Web agents are increasingly deployed to complete tasks autonomously on real websites, where adversarially injected content can induce them to perform unauthorized actions.SciGraphSelect: Auditable Scientific Data Selection through Knowledge--Reasoning Graphs
Scientific data selection is typically driven by relevance or utility scores, providing limited insight into why a document is retained.SAT-ACT: Learning CDCL Branching from Outcome-Derived Action Preferences
Learning-based approaches have increasingly been explored for SAT solving, with particular attention to improving branching decisions in conflict-driven clause learning (CDCL) solvers.In-Model Context Compression with Agentic Soft Tokens for Long-Horizon LLM Agents
Long-horizon LLM agents play an important role in solving complex and sustained tasks, with ever-growing interaction contexts.Self-Improvement with Auxiliary Rewards: Learning from Verified Traces and Evaluating Transfer
Answer-level rewards cannot distinguish reasoning traces with equally correct outcomes.Subliminal Reinforcement Learning: traits travel through a judge's scores
Subliminal learning, the transfer of a model's trait through data with no semantic trace of it, has been shown for students trained on a teacher's text.ART of PIV: Agentic Real-Time Particle Image Velocimetry for Active Flow Control
Particle image velocimetry (PIV) measures fluid motion from images of tracer particles, but its accuracy depends on choices throughout the estimation pipeline, including image preprocessing, flow…Erase the Injected Region: Multimodal Prompt-Injection Defense with On-Policy Self-Distillation
Multimodal indirect prompt injection embeds malicious instructions in external media that also contains information needed for the user's task.SERIAL-7: Deriving, Realizing, and Preserving Machine-Verifiable Outputs Across Representations
Large language models increasingly generate structured outputs consumed by programs and downstream systems, where semantic correctness alone does not guarantee reliable execution.GenDSR: Transferring Representations from Video Generation Models for Dynamic Spatial Reasoning
Dynamic spatial reasoning is essential for connecting visual intelligence to thephysical world, yet remains challenging for vision-language models (VLMs), which must preserve scene state while…Transferring Peptide-Target Interaction Patterns to Small Molecules by Joint Guidance for Diffusion and Flow Matching
Generating small molecules to target protein-protein interactions (PPIs) remains one of the most challenging yet high-reward frontiers in drug discovery.With foundation-model features, aggregator complexity does not improve cross-hospital discrimination in gastric whole-slide image classification
Whole-slide image classifiers are usually developed within one hospital and often go untested at unseen hospitals.