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Artificial Intelligence
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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 180
ConCI: A Controlled Counterfactual Benchmark for Contextual Integrity in LLMs
Contextual integrity (CI) holds that the appropriateness of sharing personal information depends on the context of the information flow, not on the information alone.GazeAct: A Human-Gaze-Annotated Manipulation Dataset for Attention-Regularized Policies
Vision-language-action (VLA) policies must ground language instructions in the right objects, contact points, and target locations for reliable manipulation.$M^2Net$: Unifying Scale-Specific Structures and Prototype Decomposition for Spatial-Temporal Forecasting
Spatial-temporal forecasting is pivotal for intelligent urban management yet remains challenging due to the intricate coupling of spatial dynamics and temporal non-stationarity.Axiomatic World Modeling for Physics Reasoning
Recent research-level physics-reasoning benchmarks for LLMs reveal a failure mode that lies not in knowledge or execution, but in modeling the world being reasoned about.HABIT-Bench: Evaluating Habit Induction from Longitudinal Weak Evidence in Agent Memory
In long-term interactions with large language model (LLM) agents, users reveal habits through their choices and actions.Comparing Sparsified MLPs and Transcoders: Many Transcoder Features Are Neurons in Disguise
MLP neurons in transformer language models are widely understood to be polysemantic, motivating transcoders - sparse, learned approximations of MLP layers - as interpretable replacement models for…Rethinking EEG Spatial Super-Resolution as Dynamic State Decomposition and Filtering
EEG spatial super-resolution aims to recover high-density neural signals from sparse electrode observations.Contrastive Hypergraph Source-free Domain Adaptive Object Detection in Adverse Weather Conditions--Extended Version
Adverse weather conditions such as fog, rain, snow, and low illumination introduce structured visibility degradations that severely impair object detectors trained on clear-weather data.When Code Becomes an LLM Call: An Empirical Study of Call-Site Contracts in Agentic Systems
Software quality has long rested on specifications that state what code must do, and on testing and verification that check that the code does it.CARVS: A Congestion-Aware Algorithm for Online Multi-Agent Pickup-and-Delivery in Human-Collaborative Warehouses
Intelligent warehouse systems have transformed logistics by integrating robots with minimal infrastructure changes, boosting efficiency and optimizing workflows compared to traditional human-only…From Stories to Features: Scaling Concept Vectors for AI Alignment & Interpretability
We study feature vectors: directions in a language model's activation space that correspond to human-interpretable concepts, such as honesty or deception.ASR Personalization in Pathological Voice: Accuracy, Efficiency, and Duration Effects
Automatic Speech recognition (ASR) struggles with Pathological speech due to persistent speaker-specific mismatch.Concordance Plausibility Check for Intervention-Conditioned Human Digital Twins
Intervention-conditioned human digital twins predict treatment alternatives that cannot be observed in the same patient.Scene-Adaptive VLA: Efficient Autonomous Driving via Dynamic Layer Routing
Vision-Language-Action (VLA) models offer a promising paradigm for autonomous driving.CADS: Measuring the Incremental Contribution of LLM Proposers in Sequential Biological Screens
Large language models are increasingly used to guide sequential biological screens, yet standard evaluations rely on raw hit counts that conflate a proposer's value with the discovery capacity of…AdamPM: Memory-Efficient LLM Optimization via Moment Pooling
Adam is widely used for training large language models (LLMs) owing to its strong optimization performance and training stability, but its element-wise estimation for the first and second moments…Severity-Channel Conditioning: An Injection-Level Study for Consumer-Device Deblurring
Motion-deblurring models lose substantial accuracy when transferred from professional cameras to smartphone-derived imagery.HSPR: Recovering Software-Agent Benchmark Scores via Hierarchical Posterior Inference
Evaluating software agents on a full benchmark is expensive.How Much Do Activation Monitors Benefit from Original Model Computations?
One powerful way to safeguard AI systems is to monitor their internal computations--where signs of undesirable behavior might be more easily detectable than from models' inputs and outputs alone.Muse Glimmer 30B: An On-Device Agentic Model
We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware.