AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIagentsMulti-Agent Design Assistant for the Simulation of Inertial Fusion Energy
arXiv:2510.17830v3 Announce Type: replace-cross Abstract: Inertial fusion energy promises nearly unlimited, clean power if it can be achieved. However, the design and engineering of fusion systems requires controlling an…
- arXiv cs.AIresearchPOPI: Personalizing LLMs via Optimized Natural Language Preference Inference
arXiv:2510.17881v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are typically aligned with population-level preferences, despite substantial variation across individual users. We introduce POPI, a…
- arXiv cs.AIresearchMetamodel-Guided Model Generation with Layered Constraints
arXiv:2510.25890v4 Announce Type: replace-cross Abstract: Large language models (LLMs) enable natural-language interaction in engineering modeling, but generated models may violate structural constraints, domain rules, o…
- arXiv cs.AIresearchSTAR-VAE: A Scalable Latent-Variable Transformer for Controllable Molecular Generation
arXiv:2511.02769v2 Announce Type: replace-cross Abstract: Many molecular Transformers lack probabilistic latent variables for posterior inference and latent interpolation. We introduce STAR-VAE, a SELFIES-encoded, Transf…
- arXiv cs.AIresearchFinding Kissing Numbers with Game-theoretic Reinforcement Learning
arXiv:2511.13391v5 Announce Type: replace-cross Abstract: Since Isaac Newton first studied the Kissing Number Problem in 1694, determining the maximal number of non-overlapping spheres around a central sphere has remaine…
- arXiv cs.AIresearchTowards Synergistic Teacher-AI Interactions with Generative Artificial Intelligence
arXiv:2511.19580v2 Announce Type: replace-cross Abstract: Generative artificial intelligence (GenAI) is increasingly used in education, posing significant challenges for teachers adapting to these changes. GenAI offers u…
- arXiv cs.AIresearchRadiance-Field Guided Pretraining: Scaling Localization Models with Unlabeled Wireless Signals
arXiv:2512.07309v2 Announce Type: replace-cross Abstract: Radio frequency (RF)-based indoor localization offers significant promise for applications such as indoor navigation, augmented reality, and pervasive computing.…
- arXiv cs.AIresearchA Multimodal Large Language Model-Driven Framework for Context-Aware UAV Emergency Landing Site Selection
arXiv:2602.01163v2 Announce Type: replace-cross Abstract: Safe UAV emergency landing requires more than just identifying flat terrain; it demands understanding complex semantic risks (e.g., crowds, temporary structures)…
- arXiv cs.AIresearchSWE-Universe: Scale Real-World Verifiable Environments to Millions
arXiv:2602.02361v2 Announce Type: replace-cross Abstract: We propose SWE-Universe, a scalable and efficient framework for automatically constructing real-world software engineering (SWE) verifiable environments from GitH…
- arXiv cs.AIresearchDiscovering Data Manifold Geometry through Geometric Properties
arXiv:2602.02611v2 Announce Type: replace-cross Abstract: A prevailing paradigm in modern representation learning is the map-first approach, in which a representation map is learned from reconstruction, embedding, or tas…
- arXiv cs.AIresearchFMMD: A multimodal multidisciplinary dataset of open peer reviews from F1000Research
arXiv:2602.14285v2 Announce Type: replace-cross Abstract: Automated scholarly paper review (ASPR) has entered the coexistence phase with traditional peer review, where artificial intelligence (AI) systems are increasingl…
- arXiv cs.AIresearchReal Money, Fake Models: Deceptive Model Claims in Shadow APIs
arXiv:2603.01919v3 Announce Type: replace-cross Abstract: Access to frontier large language models (LLMs), such as GPT-5 and Gemini-2.5, is often hindered by high pricing, payment barriers, and regional restrictions. The…
- arXiv cs.AIresearchSpectral Overfitting in Noisy Linear Probing of Pretrained Representations
arXiv:2603.02293v3 Announce Type: replace-cross Abstract: Frozen pretrained features are often treated as a safe interface for downstream learning: only a small linear readout is trained, while the backbone is fixed. We…
- arXiv cs.AIresearchTowards Effective Orchestration of AI x DB Workloads
arXiv:2603.03772v2 Announce Type: replace-cross Abstract: AI-driven analytics are increasingly crucial to data-centric decision-making. Executing relational and AI operators in separate runtimes prevents the database opt…
- arXiv cs.AIresearchSeparators in Enhancing Autoregressive Pretraining for Vision Mamba
arXiv:2603.03806v2 Announce Type: replace-cross Abstract: The state space model Mamba has recently emerged as a promising paradigm in computer vision, attracting considerable attention for its efficient handling of long-…
- arXiv cs.AIresearchSeeing the imagined: latent functional alignment in visual imagery decoding from fMRI data
arXiv:2604.15374v2 Announce Type: replace-cross Abstract: Recent progress in visual brain decoding from fMRI has been enabled by large-scale datasets such as the Natural Scenes Dataset (NSD) and powerful diffusion-based…
- arXiv cs.AIagentsA Survey on Long-Term Memory Security in LLM Agents: Attacks, Defenses, and Governance Across the Memory Lifecycle
arXiv:2604.16548v5 Announce Type: replace-cross Abstract: The emergence of writable, cross-session persistent memory in LLM agents introduces a qualitatively different threat landscape from conventional input-centric sec…
- arXiv cs.AIresearchFaithful Autoformalization via Roundtrip Verification and Repair
arXiv:2604.25031v3 Announce Type: replace-cross Abstract: When an LLM formalizes natural language, how do we know the output is faithful? We propose a roundtrip verification approach which does not require ground-truth a…
- arXiv cs.AIresearchLearning Dynamic Evidence Routes for Vision Transformer Probing
arXiv:2605.00915v3 Announce Type: replace-cross Abstract: Probing frozen vision transformers typically uses permutation-invariant aggregation (GAP or $\texttt{[CLS]}$), treating patch tokens as an unstructured set. Conte…
- arXiv cs.AIresearchLLM Ghostbusters: Surgical Package Hallucination Suppression via Adaptive Unlearning
arXiv:2605.01047v2 Announce Type: replace-cross Abstract: Hallucinations remain an unsolved problem for LLMs, and package hallucinations are a particularly dangerous instance of this phenomenon. Package hallucinations oc…
- arXiv cs.AIresearcheXplaining to Learn (eX2L): Regularization Using Contrastive Visual Explanation Pairs for Distribution Shifts
arXiv:2605.06368v2 Announce Type: replace-cross Abstract: Despite extensive research into mitigating distribution shifts, many existing algorithms yield inconsistent performance, often failing to outperform baseline Empi…
- arXiv cs.AIagentsMechanism Design Is Not Enough: Prosocial Agents for Cooperative AI
arXiv:2605.08426v3 Announce Type: replace-cross Abstract: Ensuring that AI agents behave safely and beneficially when interacting with other parties has emerged as one of the central challenges of modern AI safety. While…
- arXiv cs.AIagentsThe Bystander Effect in Multi-Agent Reasoning: Quantifying Cognitive Loafing in Collaborative Interactions
arXiv:2605.10698v2 Announce Type: replace-cross Abstract: Multi-agent systems (MAS) assume that collaborating inherently improves Large Language Model (LLM) reasoning. We challenge this by demonstrating that simulated so…
- arXiv cs.AIresearchUnbiased Gradients, Moving Stability Boundaries: Exact Mini-Batch Geometry in Linear Self-Attention
arXiv:2605.21292v2 Announce Type: replace-cross Abstract: Unbiased stochastic gradients can match the full gradient in expectation while changing finite-step stability. We study this effect in one-layer linear self-atten…
- arXiv cs.AIagentsAgenticDiffusion: Multi-View Reasoning with View-Conditioned Diffusion Planning for Vision-Based UAV Navigation
arXiv:2606.04111v2 Announce Type: replace-cross Abstract: Vision-based UAV navigation becomes challenging when navigation targets are distributed across complementary camera views and cannot be reliably observed from a s…
- arXiv cs.AIresearchLearning Urban Access Costs from Origin-Destination Flows via Inverse Optimal Transport
arXiv:2606.14157v2 Announce Type: replace-cross Abstract: Cities deliver basic services through mixed public-private facility networks, including schools, clinics, transit providers, and subsidized service points. In the…
- arXiv cs.AIresearchWhen Good Verifiers Go Bad: Silent Negative Transfer in Verifier-Guided VLM Training
arXiv:2606.14629v3 Announce Type: replace-cross Abstract: Verifier reliability is not portable across tasks. A verifier-guided self-DPO pipeline with genuine held-out gains on MathVista (+9.6 points on self-training data…
- arXiv cs.AIresearchFinRED: An Expert-Guided Benchmark Generation and Evaluation Framework for Financial LLM Red-Teaming
arXiv:2606.19887v4 Announce Type: replace-cross Abstract: Existing safety benchmarks target general adversarial scenarios but miss finance-specific risks. Financial LLMs face regulatory compliance violations, fraud facil…
- arXiv cs.AIresearchExplanation-Guided Medical Named Entity Recognition with Stability and Boundary Awareness for Atopic Dermatitis
arXiv:2606.22886v2 Announce Type: replace-cross Abstract: Objective: This study aims to improve the reliability and robustness of medical named entity recognition (NER) in Chinese atopic dermatitis (AD) clinical texts th…
- arXiv cs.AIresearchSOLAR: AI-Powered Speed-of-Light Performance Analysis
arXiv:2606.26383v2 Announce Type: replace-cross Abstract: How fast could a deep-learning model run on target hardware, and how far is today's implementation from that limit? These questions are central to software, hardw…
- arXiv cs.AIresearchConditional Co-Ablation: Recovering Self-Repair Backups in Transformer Circuits
arXiv:2607.01940v3 Announce Type: replace-cross Abstract: Mechanistic interpretability seeks to explain transformer behavior through circuits: sets of internal components that causally support a behavior. However, self-r…
- arXiv cs.AIresearchReasonLab: A Controlled and Auditable Evaluation of Prompting Techniques for Multiple-Choice QA
arXiv:2607.14109v2 Announce Type: replace-cross Abstract: Probing the capabilities of Large Language Models (LLMs) and building robust solutions for Multiple-Choice Question Answering (MCQA) remain central challenges in…
- arXiv cs.AIresearchFrom Plausible to Actionable: A Position on LLM Self-Explanations
arXiv:2607.15957v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) can generate natural language explanations that rationalize their own decisions, a phenomenon commonly referred to as self-explanatio…
- arXiv cs.AIresearchA Methodology for Auditable Trustworthiness Levels in AI Lifecycle Governance
arXiv:2607.16130v2 Announce Type: replace-cross Abstract: AI governance increasingly requires judgments about whether an AI system remains adequately trustworthy over time, whether observed changes are tolerable, and how…
- arXiv cs.AIresearchSemi-Automated Detection of Gaps in LLM Security Knowledge
arXiv:2607.18496v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for a range of software, hardware and human-centered security tasks. Consequently, LLM performance on security…
- arXiv cs.AIresearchParameter-Free Dynamic Regret under Heavy-Tailed Noise
arXiv:2607.27073v3 Announce Type: replace-cross Abstract: We study online convex optimization with one unbiased stochastic subgradient per round and noise having a finite $p$-th central moment, where $p\in(1,2]$ is unkno…
- arXiv cs.AIresearchCorePath: A Breast-Specialized Pathology Foundation Model for Core Needle Biopsy Diagnosis and Risk-Controlled Report Generation
arXiv:2608.03079v2 Announce Type: replace-cross Abstract: Breast core needle biopsy (CNB) is central to breast cancer diagnosis yet remains challenging because limited tissue sampling, lesion heterogeneity, and subtle mo…
- arXiv cs.AIagentsHLSmith: An Expert-Guided Agentic Framework for C/C++-to-HLS Translation
arXiv:2608.06791v2 Announce Type: replace-cross Abstract: Application-specific FPGA accelerators offer substantial performance and energy-efficiency gains across many application domains, but developing them is costly, o…
- arXiv cs.AIresearchAre Concept Bottleneck Models Effective as Decision-Support Systems?
arXiv:2608.25581v2 Announce Type: replace-cross Abstract: Concept Bottleneck Models (CBMs) are interpretable-by-design neural networks that detect human-understandable concepts from the input and use them to generate pre…
- arXiv cs.AIresearchQuery-Side Attacks on GNN-Based KGQA: Tracing Failures from Entity Linking to Answer Generation
arXiv:2608.25922v2 Announce Type: replace-cross Abstract: GNN-based Knowledge Graph Question Answering (KGQA) pipelines process queries through four discrete stages: entity linking, subgraph retrieval, GNN reasoning, and…
- arXiv cs.AIresearchGVS5H: Zero-Shot Self-Orchestration with Ledger-Based Control for Improved LLM Coding Performance
arXiv:2608.26480v2 Announce Type: replace-cross Abstract: Frontier coding performance is typically attained with large, costly proprietary models. We introduce ledger-based zero-shot self-orchestration (GVS5H), a trainin…
- arXiv cs.AIresearchCompositional Failure in Audio-Visual LLMs: Late-Layer Prior Dominance Under Cross-modal Conflict
arXiv:2608.27785v2 Announce Type: replace-cross Abstract: We study audio-visual conflict as a compositional generalization test for AV-LLMs: the model must combine synchronized but semantically incompatible audio and vid…
- arXiv cs.AIresearchIntrinsic Interaction Geometry Controls the Low-Rank Complexity of Softmax Attention
arXiv:2608.28150v2 Announce Type: replace-cross Abstract: How much matrix rank is required to preserve every bounded value output of normalized softmax attention? We study the unrestricted maximum-row-\(\ell_1\) approxim…
- arXiv cs.AIresearchHBQ: Hierarchical Scaling Block Quantization with Hardware-Efficiency-Aware Design for Accurate LLM Inference
arXiv:2609.00450v2 Announce Type: replace-cross Abstract: Block Quantization (BQ) enables efficient LLM inference by quantizing both weights and activations, but its design space remains underexplored. Through hardware-a…
- arXiv cs.AIagentsPlan Pointers and Record-Directive Form in Budgeted Verification of Inherited Agent Memory
arXiv:2609.03450v2 Announce Type: replace-cross Abstract: A model that inherits one-line memories may pull one archived source record before acting; a directive in the store can steer that pull: a pointer, a criterion or…
- arXiv cs.AIagentsWhen Users Don't Ask: Benchmarking Context-Driven Memory Retrieval in Conversational Agents
arXiv:2609.03467v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increas- ingly deployed as long-horizon conversational agents, motivating growing interest in mem- ory systems. However, existing…
- arXiv cs.AIresearchTree species mapping in Denmark: A comparison of spectral-temporal features with geospatial foundation model embeddings
arXiv:2609.03480v3 Announce Type: replace-cross Abstract: We map tree species across Denmark using National Forest Inventory plots and EO data, while evaluating the potential of foundation models for large-scale forest c…
- arXiv cs.AIresearchMonadic Second-Order Logic in HOL: Deep and Shallow with Automated Faithfulness (Extended Preprint)
arXiv:2609.07345v3 Announce Type: replace-cross Abstract: In Isabelle/HOL, we apply the deep-and-shallow embedding methodology of our prior work to monadic second-order logic (MSO). Three embeddings are developed side by…
- arXiv cs.AIresearchRice's Theorem under Self-Modification: Elevation Operators and a Normal Form
arXiv:2609.11326v3 Announce Type: replace-cross Abstract: We ask whether it can be certified algorithmically that a self-modifying program keeps a behavioural property, a safety property in the motivating case, after its…
- arXiv cs.AIresearchThe Last AI Built by Humans: Toward Genuine Recursive Self-Improvement
arXiv:2609.11873v3 Announce Type: replace-cross Abstract: Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that improve both their capabilities and the process o…