AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchReasoning with Neural Cellular Automata
arXiv:2609.36126v1 Announce Type: cross Abstract: Modern AI architectures used to solve visual reasoning tasks typically rely heavily on global connectivity and synchronization. As biological systems demonstrate, though,…
- arXiv cs.AIresearchAccessible, but Not Adopted: Increasing LLM Adoption among First-generation, Low-income (FGLI) College Students beyond Expanding Access
arXiv:2609.36129v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly positioned as a force to empower underserved communities, and significant efforts are being made to expand access. Yet, acce…
- arXiv cs.AIagentsLanguage Models Are "Insecure" Reporters
arXiv:2609.36139v1 Announce Type: cross Abstract: As large language models are deployed in increasingly autonomous long-horizon tasks, manually auditing and verifying the actions, artifacts, and outputs of models becomes…
- arXiv cs.AIresearchEncoder-Sharing Hierarchical Federated Multi-Task Learning for VANETs
arXiv:2609.36157v1 Announce Type: cross Abstract: Most federated learning frameworks for vehicular ad hoc networks assume that all vehicles collaboratively train a single model for a common task. This assumption limits t…
- arXiv cs.AIagentsFrom Dead Code and Static Requirements to Working Engines: Software Revival with Coding Agents
arXiv:2609.36161v1 Announce Type: cross Abstract: Can coding agents restore software that no longer runs while preserving its underlying methods, and reconstruct industrial software engines from open specifications? Here…
- arXiv cs.AIresearchAdversarial Debiasing of Machine Learning Models for Enhanced Network Security against DDoS Attacks
arXiv:2609.36167v1 Announce Type: cross Abstract: Distributed Denial of Service attacks are a growing threat to network infrastructure, and new techniques, including the use of generative AI, make them harder to detect.…
- arXiv cs.AIresearchDraft in Parallel, Condition Through Depth: Adjacent Causal Injection for Speculative Decoding
arXiv:2609.36173v2 Announce Type: replace-cross Abstract: Parallel speculative drafting generates multiple candidates in one backbone pass, but independent token selection can produce inconsistent continuations that shor…
- arXiv cs.AIagentsTargeting Pivotal Decisions for Credit Assignment in Agentic Reinforcement Learning
arXiv:2609.36178v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) has become a promising approach for training large language model agents. However, its uniform assignment of trajectory-level ad…
- arXiv cs.AIresearchPreviewDiff: Multimodal Critic-Guided Search over Diffusion Latents
arXiv:2609.36199v1 Announce Type: cross Abstract: Diffusion models can produce striking images and videos, but they still struggle with the compositional details that make a generation faithful to a prompt, such as objec…
- arXiv cs.AIagentsSCOUT: Synergizing Reasoning and Tool-Use for Computer-Use Safety
arXiv:2609.36201v1 Announce Type: cross Abstract: Computer-use agents (CUAs), while capable of completing computer tasks in everyday and professional workflows, can cause unintended harm even under benign instructions an…
- arXiv cs.AIresearchRepresentable but Unlearned: Encoding Rank and the Interaction-Prediction Floor
arXiv:2609.36208v1 Announce Type: cross Abstract: Input encodings can restrict which measured contrasts a predictor can jointly reproduce, even when no single contrast is forced to vanish. We compute the attainable contr…
- arXiv cs.AIresearchCineSubBench: Evaluating LLMs on Long-Form Narrative and Cultural Understanding from Multilingual Movie Subtitles
arXiv:2609.36218v1 Announce Type: cross Abstract: Large language models are increasingly evaluated in specialized domains such as law, medicine, software engineering, and cybersecurity, yet film remains comparatively und…
- arXiv cs.AIresearchMutually Adversarial Self-Training with Evolving Data for Unified Multimodal Models
arXiv:2609.36224v1 Announce Type: cross Abstract: Unified multimodal models (UMMs) combine image generation and visual understanding in a shared backbone. Since generation and understanding are inverse tasks, recent stud…
- arXiv cs.AIresearchThink Before You Restore: Risk-Aware Manchu Manuscript Restoration with Stroke-Guided Attention
arXiv:2609.36243v1 Announce Type: cross Abstract: Full-page blind restoration of historical Manchu manuscripts is challenging due to scarce annotations, unknown degradation regions, and fragile connected strokes. Generic…
- arXiv cs.AIresearchPopulation Fidelity: Evaluating Population Representativeness in LLMs
arXiv:2609.36253v1 Announce Type: cross Abstract: Large language models (LLMs) show considerable potential in simulating human attitudes and preferences. Prior work finds that LLM-generated responses can compress the ran…
- arXiv cs.AIresearchPaired Multimodal Scaling Laws
arXiv:2609.36263v1 Announce Type: cross Abstract: Existing multimodal scaling laws fit multimodality terms empirically after testing and never vary how much data is multimodally paired at fixed data budgets. We investiga…
- arXiv cs.AIresearchIn-Context Learning Amplifies a Latent Symbolic Circuit
arXiv:2609.36265v1 Announce Type: cross Abstract: Large language models can learn abstract rules from just a few in-context examples, but how their internal mechanisms activate as examples accumulate is not well understo…
- arXiv cs.AIresearchProofs Without Nominals: G\"odel's Ontological Argument, its Shallow Embedding, and the Open Questions of the Monatshefte Notes
arXiv:2609.36279v4 Announce Type: replace-cross Abstract: The shallow embedding of higher-order modal logic in classical higher-order logic, used in Benzm\"uller and Scott's Notes on G\"odel's and Scott's variants of the…
- arXiv cs.AIresearchHow Much Prompt Is Enough? A Blackbox Minimization of Few-Shots in LLMs
arXiv:2609.36289v1 Announce Type: cross Abstract: Prompts are the primary mechanism for directing the behavior of large language models (LLMs). Yet the internal structure and causal hierarchy of prompts remain poorly und…
- arXiv cs.AIresearchMoRE: Scaling mixture of experts with hardware-aware low-rank routing
arXiv:2609.36301v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) layers are central to frontier language models, and recent architectures push toward more and smaller experts. In this regime, the standard linea…
- arXiv cs.AIresearchPyroStack: A Multi-Band Spatio-Temporal Sub-Daily Dataset for Wildfires in the United States
arXiv:2609.36315v1 Announce Type: cross Abstract: Wildfires are an increasing hazard to ecosystems, air quality, and human systems, creating a growing need for datasets that support systematic development and evaluation…
- arXiv cs.AIresearchTraining LLMs to Verbalize Evaluation Awareness
arXiv:2609.36316v1 Announce Type: cross Abstract: Evaluation awareness (EA) can cause large language models (LLMs) to behave differently during audits than in deployment, yet measuring and accounting for EA remains chall…
- arXiv cs.AIresearchPeriodic Weak Spots: Phase Sensitivity from Chunked KV-Cache Compression
arXiv:2609.36322v1 Announce Type: cross Abstract: Chunked KV-cache compression reduces the memory and attention costs of long-context inference by compressing windows of consecutive tokens into fewer cache entries at a f…
- arXiv cs.AIresearchDecoyTrace: Toxic Decoys for Active Defense in Decentralized Federated Learning
arXiv:2609.36330v1 Announce Type: cross Abstract: Decentralized Federated Learning (DFL) eliminates the central aggregation server, reducing the single point of observation that traditional defenses against attacks rely…
- arXiv cs.AIresearchCalibrating One-Round Membership Inference with Neighbors
arXiv:2609.36331v1 Announce Type: cross Abstract: The state-of-the-art Membership Inference (MI) methods calibrate their signal separately for each example using reference models, auxiliary models trained to exclude the…
- arXiv cs.AIresearchATLAS: Aligned Transport of Latent Structure for Reliable World Model Planning
arXiv:2609.36333v2 Announce Type: replace-cross Abstract: Latent world models rely on representation geometry for planning, yet regularizing the latent marginal alone does not determine the state-to-state relationships u…
- arXiv cs.AIresearchRepresentation by Design in Generation: Cross-View Class-Token Alignment in Diffusion Transformers
arXiv:2609.36348v1 Announce Type: cross Abstract: Generative and representation learning remain asymmetrically connected: semantic representations are used to improve diffusion generation, whereas the models' own represe…
- arXiv cs.AIresearchExplainability from Training with Applications to TCR-Epitope Prediction
arXiv:2609.36354v1 Announce Type: cross Abstract: Deep learning models have achieved strong performance in artificial intelligence for science, yet their black-box nature limits our understanding of how they learn scient…
- arXiv cs.AIresearchCompress to Remember: Learning Compact Memory via On-Policy Distillation for Long Video Generation
arXiv:2609.36364v1 Announce Type: cross Abstract: Standard video generators do not natively compact historical context into reusable memory tokens. As generation continues, the growing history makes it increasingly diffi…
- arXiv cs.AIresearchCross-attention encoding models reveal dynamic spatiotemporal routing across human higher visual cortex
arXiv:2609.36366v1 Announce Type: cross Abstract: Understanding how the brain parses actions and events from time-varying natural inputs is a central challenge in neuroscience. Recent work has used deep neural network (D…
- arXiv cs.AIresearchAdaKerNet: Neural Kernel Decoding for Task-Adaptive Prediction with Multimodal Large Models
arXiv:2609.36368v1 Announce Type: cross Abstract: Large foundation models have been introduced with the promise of efficient adaptation to downstream tasks. Yet, under limited supervision, MLLMs, an important class of la…
- arXiv cs.AIagentsLatentSift: Policy-State Filtering for Token-Efficient Verification of Software Engineering Agents
arXiv:2609.36371v1 Announce Type: cross Abstract: Test-time scaling improves software engineering agents by generating multiple candidate trajectories and selecting the best one. Verifying and selecting among these long…
- arXiv cs.AIagentsAudience-Bound Persistent Memory: Authorization Across the Memory Lifecycle
arXiv:2609.36373v1 Announce Type: cross Abstract: A personal language agent that acts for its owner across private and shared conversations can learn a fact from one audience and later place it in the context it assemble…
- arXiv cs.AIresearchQuantization Enables Private Dense Retrieval against Malicious Service Providers
arXiv:2609.36376v1 Announce Type: cross Abstract: Dense retrieval, the key component of Retrieval Augmented Generation (RAG), retrieves the most relevant documents by comparing dense vector representations of queries and…
- arXiv cs.AIagentsReward-rate Policy Gradient for Efficient Machine Learning Engineering Agents
arXiv:2609.36393v1 Announce Type: cross Abstract: Traditional reinforcement learning (RL) techniques focus on maximizing expected cumulative reward, where each action assumes to take a constant unit of time. However, thi…
- arXiv cs.AIresearchWhere Should Physics Enter a Molecular Crystal Generator?
arXiv:2609.36398v1 Announce Type: cross Abstract: Generative models make molecular crystal structure prediction fast, but their samples still exhibit geometric and packing violations. Physics can be introduced during tra…
- arXiv cs.AIresearchCalibrated to Whom? Persona and Language Effects on Cultural Values in JEV
arXiv:2609.36399v2 Announce Type: replace-cross Abstract: Decision-only language models return a probability for every answer option instead of generating text, which makes them attractive as survey respondents and as ju…
- arXiv cs.AIresearchLonger Records, Broader Invariance: The Hidden Scaling Problem in Longitudinal Contrastive Learning
arXiv:2609.36409v1 Announce Type: cross Abstract: Longitudinal data are valuable because people change. Yet the objectives used to learn from these data can inadvertently erase that change. In person-level contrastive le…
- arXiv cs.AIresearchFineART: Fine-Grained Annotated Robotic Trajectory Dataset and Vision-Language-Action Model for Bimanual Manipulation
arXiv:2609.36416v3 Announce Type: replace-cross Abstract: Robots operating in real-world environments must often execute complex, multi-step bimanual tasks over long horizons rather than single, isolated actions. Current…
- arXiv cs.AIresearchOnline Versatile Incremental Learning: Towards Class and Domain-Agnostic Adaptation at Any Time
arXiv:2609.36442v1 Announce Type: cross Abstract: Continual learning enables vision systems to adapt to ever-changing data distributions. Despite significant advances, existing approaches fail to capture continuous and c…
- arXiv cs.AIresearchReliable Parallel Decoding in Masked Diffusion Language Models
arXiv:2609.36452v1 Announce Type: cross Abstract: Masked diffusion language models (MDLMs) can generate text efficiently by predicting multiple masked tokens in parallel, but predictions from the same forward pass are no…
- arXiv cs.AIresearchChannel-Dependent State Space Model for Multivariate Time Series Forecasting
arXiv:2609.36453v2 Announce Type: replace-cross Abstract: Multivariate time series forecasting (MTSF) is critical across many real-world domains. Existing deep learning approaches fall into two paradigms with distinct li…
- arXiv cs.AIresearchEmergent Tonal Structure in Learned Chord Embeddings and Its Relation to Tonal Tension
arXiv:2609.36460v1 Announce Type: cross Abstract: Several tonal pitch spaces and computational models have been proposed to analyze tonal structure in Western tonal music, many of them grounded in principles from music t…
- arXiv cs.AIresearchStaircase Policy: Streaming Inference for World-Action Models with Large Action Chunks
arXiv:2609.36471v1 Announce Type: cross Abstract: World-Action Models (WAMs) improve robotic manipulation by conditioning action generation on predicted future observations, but future prediction adds further inference o…
- arXiv cs.AIresearchSimilar Choices, Different Attention: Cross-Modal Associations in Humans and Vision-Language Models
arXiv:2609.36475v1 Announce Type: cross Abstract: Cross-modal associations are systematic pairings of features across modalities, such as the association of 'bouba' with round shapes and 'kiki' with sharp shapes. Prior w…
- arXiv cs.AIresearchGuard Models Are Overconfident Where Base Models Are Uncertain
arXiv:2609.36477v1 Announce Type: cross Abstract: Guard models are used as safety classifiers, with confidence scores driving downstream moderation decisions. We evaluate five guard models for prompt classification and f…
- arXiv cs.AIresearchQuantum Computing for Network Security Classification: Near-Term Classification and Long-Term Memory Efficiency
arXiv:2609.36479v1 Announce Type: cross Abstract: Quantum computing has already been explored in several network-security applications. However, how quantum computing may contribute to network-security classification in…
- arXiv cs.AIagentsLLMs Learn to Evade Latent Monitors from Prior Feedback Alone
arXiv:2609.36490v1 Announce Type: cross Abstract: Latent space monitors aim to detect undesired behaviors in LLM agents by inspecting an agent's internal activations rather than its outputs. However, interactive monitori…
- arXiv cs.AIresearchBenchmarking Vision-Language Models on Synapse and Neuron Proofreading in Connectomics
arXiv:2609.36492v2 Announce Type: replace-cross Abstract: We benchmarked vision-language models (VLMs) on the decisions annotators take when inspecting electron microscopy images in connectomics: synapse proofreading (pr…
- arXiv cs.AIresearchInterBias-SV: Compound Conditions in Speaker Verification
arXiv:2609.36500v1 Announce Type: cross Abstract: Speaker verification systems encounter combinations of noise, channel distortion, and changes in speech. Evaluating each condition separately does not establish whether t…