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Monday 19 October
- PaperMotor compound fault diagnosis using an attention-based cross-talk architecture
As physical AI increasingly relies on sensing to understand physical systems, reliable condition monitoring of industrial machinery has become more important. Motors are
- PaperManifold-Constrained Residual Adaptation with Frame-Adaptive Layer Aggregation for Speaker Verification
Large self-supervised speech models provide powerful representations for speaker verification, but full fine-tuning is expensive. Most conventional adapters insert small
- PaperRethinking Sparse-View 3D Gaussian Splatting: A Few-Shot Learning Perspective on Overfitting Prevention
Sparse-view novel view synthesis (NVS) is essential for AR/VR and real-time communication applications, yet remains challenging when reconstructing 3D scenes from limited
- PaperLearn the Interface, Not the Implementation: Output Representation Dominates Training Regime in LLM-Based RTL Generation
Large-language-model register-transfer-level (RTL) generation has concentrated on how to train the model: fine-tuning, continued pre-training, and reinforcement learning
- PaperAsynchronous On-Policy Self-Distillation
Unlike on-policy distillation (OPD), which depends on a separate teacher model, on-policy self-distillation (OPSD) leverages a single language model acting simultaneously
- PaperDeltaTrace: Efficient Signed Attribution for Reasoning Language Models
We study how words in the context support or oppose a language model's response and present DeltaTrace, a novel attribution framework that explains the effect of input to
- PaperLearning to Reason Efficiently with Interventional Step Credit
Large reasoning models often produce lengthy chain-of-thought (CoT) traces mixing useful intermediate steps with unnecessary ones. Recent methods explore step-level signa
- PaperVision-Language-Delta-Action: Learning Compact Deltas as Actionable Transition Interfaces for Robotic Manipulation
Robotic manipulation is not merely observation-to-action generation, but the realization of task-specified state changes in the physical world. Existing vision-language-a
- PaperResidual-Guided Adaptive Tucker Rank Allocation for Parameter-Efficient MCI Conversion Prediction
Allocating limited trainable capacity across convolutional layers is a central challenge in parameter-efficient fine-tuning (PEFT) of pretrained three-dimensional (3D) ne
- PaperCODA: Cohort- and Drift-aware Foundation Model for Multimodal Clinical Reasoning
Recent advances in multimodal foundation models have demonstrated strong performance across diverse clinical tasks. However, existing approaches predominantly operate at
- PaperBenefit-Targeted Routing and Bounded Revision for LLM-Based Evidence Screening in Manufacturing Supplier Discovery
An evidence-review system must allocate additional model judgments and control their use. We study these software decisions on 6,164 frozen manufacturing source-task pair
- PaperMinimum-Cost Robust Evidence Certificates for Horn Reasoning under Correlated Source Failures
A small justification for a rule-based conclusion may disappear when a source is withdrawn, and multiple derivations need not provide independent evidence. We study minim
- PaperActionRoPE: Action as Coordinates for Spatially Consistent Control in Planar-Camera Game World Models
Game world models have made rapid progress toward real-time interactive generation. Yet action control is still predominantly implemented as feature conditioning, leaving
- PaperAdaptive Decoding Methods for Token-Efficient Reinforcement Learning
Rollout decoding affects both which trajectories are used for reinforcement learning with verifiable rewards (RLVR) and how many completion tokens are spent collecting th
- PaperAre Self-Evolving Agents Continual Learners?
Large language model agents are often deployed in environments where new knowledge, tools, and workflows keep arriving. Such an agent is therefore expected to adapt conti
- PaperStatistical Learning Theory for Direct Preference Optimization
Direct Preference Optimization (DPO) learns from pairwise preferences through a logistic objective whose score-difference parameterization follows the Bradley--Terry mode
- PaperArabic Financial NLP
Financial communication connects numerical accounts of economic activity with explanations of performance, responsibility and future expectations. Arabic financial natura
- PaperREST: Reliability-Guided Spatial Transcriptomics Supervision for Gene Expression Prediction from Histopathological HE-Stained Images
Histopathology is central to cancer diagnosis, but morphology in Hematoxylin and Eosin (HE)-stained images does not directly reveal the molecular states that characterize
- PaperMASIF: Implicit Failures for Process Observability in Multi-Agent Systems
Multi-agent systems (MAS) can complete a task despite local execution errors that are corrected, bypassed, or carried forward without individually determining its outcome
- PaperRubrics Beyond Evaluation: Exploiting Rubric Structure in Reinforcement Learning
Rubrics are widely used to evaluate open-ended question answering by breaking overall quality into explicit criteria. These explicit criteria make rubrics a rich source o
- PaperAuditing Semantic and Relational Reliability in Open-Vocabulary Human-Object Interaction Evaluation
Open-vocabulary human-object interaction detectors describe interactions in free text, and this creates a problem for evaluation. Category scoring rejects valid paraphras
- PaperACE-Trader: Adversarial Co-Evolution for Generator-Critic Trading Systems
Generator--critic trading systems pair an LLM-based trader that makes trading decisions with a red team agent that evaluates these decisions and provides feedback for rev
- PaperMeasurement Validity and Representation Dynamics of Confidence Signals in Large Language Models
Whether a language model "knows what it knows" matters for trustworthy deployment and for deciding when it should abstain. Prior work usually measures this through one ch
- PaperSWIFT: Self-guided Weak-to-strong dIFfusion models via Target extrapolation
Training high-quality diffusion models is computationally expensive, and inference-time guidance often adds further sampling cost. In this work, we introduce Swift, a sim
- PaperA Cue's Hidden Price: Auditing Seller Influence on AI Shoppers
Large language models are increasingly asked to shop on a user's behalf, which lets seller-controlled content such as badges, endorsements, and framing steer what they re
- PaperNot Every Rollout Needs Distillation: Correctness-Filtered On-Policy Self-Distillation
On-policy self-distillation (OPSD) supervises student-generated trajectories with a reference-conditioned version of the same base model. We ask whether every trajectory
- PaperOV-PEAR: Observation-Verified Pose-Scale Estimation and Reconstruction for Unknown Industrial Manipulation Objects
Fine industrial robotic manipulation requires 6D pose, scale, and an operation-ready 3D model. Existing industrial pose estimation relies on CAD models, object-specific t
- PaperWhere RL Breaks: Localizing and Repairing Failures via Targeted Continued Pretraining
Reinforcement learning with verifiable rewards (RLVR) is widely used to improve reasoning in language models, yet growing evidence suggests that it mostly sharpens what t
- PaperDiffusion Language Models Change Speed Across Tasks and Languages
Diffusion language models can write several tokens in one forward pass, and they decide during generation how many passes to spend. Two outputs of the same token length c
- PaperFrontierRefactor: Benchmarking Multi-Scale Performance-Oriented Codebase Refactoring
Autonomous codebase refactoring requires coding agents to restructure working software while strictly preserving externally observable behavior and prioritizing execution
- PaperHihaze: One-Step Diffusion for High-Resolution Real-World Image Dehazing
Diffusion models have recently achieved encouraging results in real-world image dehazing. However, restoring high-resolution images remains challenging due to spatially n
- PaperWhen Retrieval Partially Conflicts with Skills: Understanding Procedural Hallucination in Language Models
Language models increasingly use skills that provide reusable instructions and procedures for task execution. After a relevant skill has been selected, the model may need
- PaperOptimizing Marketing Budgets for Social Influence: A Generalized Fractional Incentives Framework
Marketing managers routinely allocate limited budgets across individuals in social networks whose responsiveness and influence vary substantially. We study the problem of
- PaperWhen to Stop Asking: Factor Coverage Bias and LLM Determinability Judgments with Underspecified Information in Medicine
Clinical decision-making often begins with underspecified information and requires not only gathering missing information but also knowing when to stop. This calls for ju
- PaperModal Sense Disambiguation in Language Models: The Role of Context, Training Domain, and Input Frequency
Modals such as may and must can take on different senses depending on discourse context, alternating between root interpretations (e.g., permission, obligation) and epist
- PaperDynamic Dual-Feedback Conformal Inference for Time Series Forecasting
Quantifying uncertainty in time series forecasting is particularly demanding because sequential data exhibit temporal dependence and are prone to distributional changes.
- PaperIs it RL or Data? A Controlled Comparison of GRPO and Rejection-Sampling Fine-Tuning
Bauer et al. (2026) showed that in low-data reinforcement learning with verifiable rewards, training GRPO on mixed-difficulty prompts gives up to 5x the sample efficiency
- PaperCommunication-Efficient Federated Domain Generalization in Edge Networks via Dynamic Prototype Regulation
Federated learning (FL) is a distributed paradigm for Internet of Things (IoT) edge networks. However, deploying Vision-Language Models (VLMs) over wireless edge networks
- PaperDo We Need Learned Targets? Classical Gradients as Supervision for 2D Gaussian Initialization
Learning-based Gaussian image initializers can require costly supervision obtained by per-image optimization. We investigate whether the Pseudo-PPM targets used by Instan
- PaperSector-Ring Linear Reservoirs: Sector-Wise Decay-Timescale Allocation With State Reuse Across Candidate Settings
In reservoir computing, performance depends on whether the fixed dynamics of the reservoir suit the task, and the appropriate memory length and frequency response differ
Headlines and links come from the labs' own blogs, Hacker News and the GDELT news index, and from the sources our index already follows. We show a short excerpt and always link to the original. A launch reported by a news site rather than the lab is marked “Reported” until the lab itself announces it.