AI research papers
362 papers in Research Sources, newest first, from the research feeds listed on the sources page.
- arXivResearch SourcesVariational Approach for Job Shop Scheduling
arXiv:2602.00408v3 Announce Type: replace-cross Abstract: This paper proposes a novel Variational Graph-to-Scheduler (VG2S) framework for solving the Job Shop Scheduling Problem (JSSP), a critical task in manufacturing t…
- arXivResearch SourcesHALT: Hallucination Assessment via Log-probs as Time series
arXiv:2602.02888v2 Announce Type: replace-cross Abstract: Hallucinations remain a major obstacle for large language models (LLMs), especially in safety-critical domains.
- arXivResearch SourcesBypassing the Rationale: Causal Auditing of Implicit Reasoning in Language Models
arXiv:2602.03994v3 Announce Type: replace-cross Abstract: Chain-of-thought (CoT) prompting is widely used as a reasoning aid and is often treated as a transparency mechanism.
- arXivResearch SourcesPACT-WAM: Predicting Actions and Visual Foresight with Compact Temporal Encoding for Robot Manipulation
arXiv:2602.15882v2 Announce Type: replace-cross Abstract: Robot manipulation uses temporal context to select actions and visual foresight to assess their consequences, yet dense representations of past and future observa…
- arXivResearch SourcesMind the Style: Impact of Communication Style on Human-Chatbot Interaction
arXiv:2602.17850v3 Announce Type: replace-cross Abstract: Conversational agents increasingly mediate everyday digital interactions, yet the effects of their communication style on user experience and task success remain…
- arXivResearch SourcesMINT: Multimodal Imaging-to-Speech Knowledge Transfer for Early Alzheimer's Screening
arXiv:2602.23994v2 Announce Type: replace-cross Abstract: Alzheimer's disease is a progressive neurodegenerative disorder in which mild cognitive impairment (MCI) precedes dementia.
- arXivResearch SourcesUniversal NP-Hardness of Clustering under General Utilities
arXiv:2603.00210v2 Announce Type: replace-cross Abstract: Clustering is a central primitive in unsupervised learning, yet practice is dominated by heuristics whose outputs can be unstable and highly sensitive to represen…
- arXivResearch SourcesEnhancing Physics-Informed Neural Networks with Domain-aware Fourier Features: Towards Improved Performance and Interpretable Results
arXiv:2603.02948v2 Announce Type: replace-cross Abstract: Physics-Informed Neural Networks (PINNs) incorporate physics into neural networks by embedding partial differential equations (PDEs) into their loss function.
- arXivResearch SourcesCzechTopic: A Benchmark for Zero-Shot Topic Localization in Historical Czech Documents
arXiv:2603.03884v2 Announce Type: replace-cross Abstract: Topic localization aims to identify spans of text that express a given topic defined by a name and description.
- arXivResearch SourcesAuthorMix: Modular Authorship Style Transfer via Layer-wise Adapter Mixing
arXiv:2603.23069v4 Announce Type: replace-cross Abstract: The task of authorship style transfer involves rewriting text in the style of a target author while preserving the meaning of the original text.
- arXivResearch SourcesAMIGO: Agentic Multi-Image Grounding Oracle Benchmark
arXiv:2603.28662v2 Announce Type: replace-cross Abstract: Agentic vision-language models increasingly act through extended interactions, but most evaluations still focus on single-image, single-turn correctness.
- arXivResearch SourcesCan We Still Trace L1 Signals? Investigating the Resilience of Native Language Signals in the LLM Era
arXiv:2604.08568v4 Announce Type: replace-cross Abstract: The widespread use of LLM-based writing assistance has raised an interesting question about the homogenization of English.
- arXivResearch SourcesDeep Learning for Sequential Decision Making under Uncertainty: Foundations, Frameworks, and Frontiers
arXiv:2604.11507v2 Announce Type: replace-cross Abstract: Artificial intelligence (AI) is moving increasingly beyond prediction to support decisions in complex, uncertain, and dynamic environments.
- arXivResearch SourcesVISTA: Validation-Informed Trajectory Adaptation via Self-Distillation
arXiv:2604.12044v2 Announce Type: replace-cross Abstract: Deep learning models may converge to suboptimal solutions despite strong validation accuracy, masking an optimization failure we term Trajectory Deviation.
- arXivResearch SourcesHINTBench: Horizon-agent Intrinsic Non-attack Trajectory Benchmark
arXiv:2604.13954v2 Announce Type: replace-cross Abstract: Existing agent-safety evaluation has focused mainly on externally induced risks.
- arXivResearch SourcesSchema-Key Wording as an Instruction Channel in Structured Generation under Constrained Decoding
arXiv:2604.14862v3 Announce Type: replace-cross Abstract: Constrained decoding is widely used to make large language models produce structured outputs that satisfy schemas such as JSON.
- arXivResearch SourcesHow to Compress KV Cache in RL Post-Training? Shadow Mask Distillation for Memory-Efficient Alignment
arXiv:2605.06850v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) has emerged as a crucial paradigm for unlocking the advanced reasoning capabilities of Large Language Models (LLMs), encompassing fram…
- arXivResearch SourcesEfficientTDMPC: Improved MPC Objectives for Sample-Efficient Continuous Control
arXiv:2605.16692v3 Announce Type: replace-cross Abstract: We introduce EfficientTDMPC, a sample-efficient model-based reinforcement learning method for continuous control built on the TD-MPC family of algorithms.
- arXivResearch SourcesDetect Before You Leap: Mirage Detection in Vision-Language Models
arXiv:2606.00435v4 Announce Type: replace-cross Abstract: Vision-language models (VLMs) can produce confident answers without relevant visual evidence, a failure mode known as mirage reasoning (Asadi et al., 2026).
- arXivResearch SourcesTime-Aware Diffusion based on Preference Disentanglement for Generative Recommendation
arXiv:2606.01670v2 Announce Type: replace-cross Abstract: Recently, Generative Recommenders (GRs) have emerged as a transformative recommendation paradigm by replacing traditional item IDs with semantic indices (SIDs).
- arXivResearch SourcesLibra: Efficient Resource Management for Agentic RL Post-Training
arXiv:2606.03077v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has emerged as a standard post-training paradigm for shaping large language models (LLMs) into capable agents.
- arXivResearch SourcesFLARE: Fine-Grained Diagnostic Feedback for LLM Code Refinement
arXiv:2606.03852v2 Announce Type: replace-cross Abstract: Large language models often generate code with bugs.
- arXivResearch SourcesFrom 'May' to 'Is': Certainty Distortion in Language Model Rewriting
arXiv:2606.07951v2 Announce Type: replace-cross Abstract: Humans increasingly turn to Language Models (LMs) in ways that shape beliefs and drive decisions, including discussing, rewriting, and summarizing information fro…
- arXivResearch SourcesLargeMonitor: Monitoring Online Task-Free Continual Learning via Large Pretrained Models
arXiv:2606.09430v2 Announce Type: replace-cross Abstract: Online task-free continual learning (TFCL) requires intelligent agents to sequentially accumulate knowledge from an unbounded, non-stationary data stream under st…
- arXivResearch SourcesFollow the Latent Roadmap: Navigating Revocable Decoding for Diffusion LLMs with Anchor Tokens
arXiv:2606.16847v5 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) offer a promising avenue for parallel generation but face a trade-off between decoding speed and quality.
- arXivResearch SourcesSegTME-UNI2: A Foundation Model-Based Framework for Generalisable Multiclass Cell Segmentation and LLM-Driven Tumour Microenvironment Characterisation in Histopathology
arXiv:2606.17702v3 Announce Type: replace-cross Abstract: Characterising the TME from routine H&E-stained histology images requires simultaneous cell segmentation, biological feature extraction, and interpretable clinica…
- arXivResearch SourcesSubjective Risk Decomposition: A New View for Uncertainty Quantification
arXiv:2607.15196v3 Announce Type: replace-cross Abstract: We present a novel viewpoint for uncertainty quantification.
- arXivResearch SourcesDebiasing Text-to-Image Evaluation via Implicit Cultural Alignment Reward Modeling
arXiv:2607.15740v3 Announce Type: replace-cross Abstract: As Text-to-Image (T2I) systems rapidly advance, evaluating the cultural authenticity of synthesized content has become increasingly important for fair and trustwo…
- arXivResearch SourcesAgentic Real2Sim: Physics-based World Modeling with Vision-Language Agents
arXiv:2607.19190v4 Announce Type: replace-cross Abstract: Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a streamlined real2sim pr…
- arXivResearch SourcesRiemannian Deep Learning: Modules, Networks, and Geometries
arXiv:2607.19305v4 Announce Type: replace-cross Abstract: Deep neural networks on manifold-valued representations have attracted growing interest, but many basic components remain tied to specific manifolds, rely on Eucl…
- arXivResearch SourcesPost-Training in Time Series Foundation Models: A Unifying Framework
arXiv:2607.20002v3 Announce Type: replace-cross Abstract: Time series foundation models (TSFMs) have emerged as general-purpose models for time series analysis, but pretraining alone is often insufficient for reliable do…
- arXivResearch SourcesLatency-Tolerant Cloud-Edge Collaborative Vision-Language-Action Models via Emergent Representational Specialization
arXiv:2608.00569v3 Announce Type: replace-cross Abstract: Deploying billion-parameter Vision-Language-Action (VLA) policies on mobile robots creates a systems conflict: semantic reasoning benefits from cloud GPUs, wherea…
- arXivResearch SourcesRanking Infrared-Visible Fusion the Way Humans Do: A Learned Pairwise Preference Measure
arXiv:2608.01301v4 Announce Type: replace-cross Abstract: Human pairwise comparison provides a direct basis for perceptual infrared-visible image fusion assessment, but dense annotation becomes costly as method pools gro…
- arXivResearch SourcesDeep Divide-and-Reduce in Symbolic Regression
arXiv:2608.02628v3 Announce Type: replace-cross Abstract: Symbolic regression (SR) aims to discover underlying mathematical expressions from data while preserving interpretability.
- arXivResearch SourcesExplicit Language Memory for Long-Horizon Planning in Vision-Language-Action Models
arXiv:2608.04765v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models provide a unified paradigm for connecting visual perception, language understanding, and robotic control.
- arXivResearch SourcesGoverning Agentic AI in FinTech
arXiv:2608.11344v3 Announce Type: replace-cross Abstract: Financial institutions are delegating consequential decisions to agentic AI systems that decompose goals, coordinate models and tools, and act with little oversig…
- arXivResearch SourcesUnsupervised Anomaly Detection for Image Dataset Quality Assurance in Multi-Center Breast MRI
arXiv:2608.16725v2 Announce Type: replace-cross Abstract: Corrupted, inconsistent, or anomalous data silently threatens the safety and reliability of medical AI.
- arXivResearch SourcesSafety Does Not Compose: Non-Decaying Loop State for Autonomous LLM Agents
arXiv:2608.27141v5 Announce Type: replace-cross Abstract: Large language model agents are increasingly deployed as autonomous loops.
- arXivResearch SourcesPosition Matters: Feature Inversion Attacks in ViT Split Inference with Token Reduction and Shuffling
arXiv:2609.01232v2 Announce Type: replace-cross Abstract: Vision Transformers (ViTs) are increasingly used in split-inference systems, where edge devices transmit intermediate token representations to a remote cloud.
- arXivResearch SourcesNot All Agreement Counts as Corroboration: Provenance-Conserving Multi-View Fusion for Typed Action Admission in Human-Robot Collaboration
arXiv:2609.01662v2 Announce Type: replace-cross Abstract: Better probability scores do not establish that evidence has been counted correctly.
- arXivResearch SourcesExploring the Potential of Contrastive Language-Image Pre-training for Multi-Source Remote Sensing Data
arXiv:2609.03391v2 Announce Type: replace-cross Abstract: Contrastive language-image learning (CLIP) has become a key paradigm for remote sensing vision-language understanding.
- arXivResearch SourcesCalendar-Structured Sparse Principal Component Analysis for Interpretable Multi-Periodic Electricity Consumption Profiles
arXiv:2609.06060v2 Announce Type: replace-cross Abstract: Long-term electricity-consumption profiles exhibit several simultaneous periodic structures, including daily, weekly, and annual cycles.
- arXivResearch SourcesSteering Interference Reflects the Model's Defaults, Not the Behavior Directions
arXiv:2609.06951v2 Announce Type: replace-cross Abstract: Activation steering promises modular control of language model behavior: a behavior such as politeness corresponds to a direction in a model's activations, and ad…
- arXivResearch SourcesProprioception-Anchored Cross-Modal Pretraining for Zero-Shot Sim-to-Real Contact-Rich Assembly
arXiv:2609.07534v3 Announce Type: replace-cross Abstract: Contact-rich assembly remains challenging because it requires submillimeter spatial accuracy and reliable interpretation of forces during sustained contact.
- arXivResearch SourcesAdaptive Anisotropic Attention for Axis-Structured Signals
arXiv:2609.08788v3 Announce Type: replace-cross Abstract: Dense self-attention treats all token pairs as equally plausible before learning, an interaction-isotropic prior that can be mismatched to structured signals.
- arXivResearch SourcesA Mathematical Theory of Pragmatic Information
arXiv:2609.10986v2 Announce Type: replace-cross Abstract: We propose a mathematical theory of pragmatic information that connects communication, control, and decision-making.
- arXivResearch SourcesCreating an Atomic User Model for Personality-Aware Large Language Model Interaction
arXiv:2609.12086v2 Announce Type: replace-cross Abstract: Assistants built on large language models are expected to write in their users' own voice.
- arXivResearch SourcesEvaluating Context Segmentation in Locally Deployable SLMs for Cybersecurity CTF Tasks
arXiv:2609.12839v3 Announce Type: replace-cross Abstract: The proliferation of highly capable open-weight Small Language Models (SLMs) democratizes access to advanced cybersecurity capabilities, posing an escalating risk…
- arXivResearch SourcesLanguage-Guided Terrain-Adaptive Neural MPC for Autonomous Traversal of Articulated Tracked Robots
arXiv:2609.13083v3 Announce Type: replace-cross Abstract: In urban search and rescue, articulated tracked robots (ATRs) must traverse structured but contact-rich environments such as stairwells and cluttered building int…
- arXivResearch SourcesCross-Block Conditioning in Deep Boltzmann Machines for Statistical Data Fusion
arXiv:2609.14934v2 Announce Type: replace-cross Abstract: Statistical data fusion combines two panels that share a block of covariates but observe disjoint outcome blocks, and in its traditional form no row observes both…