applications

I also agree with this comment that the current view of FDEs is likely too limited to actually catalyze organizational transformation.

applicationsethan-mollick--x

I also agree with this comment that the current view of FDEs is likely too limited to actually catalyze organizational transformation. @emollick Are they doing org change, though? The army of forward

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I think frontier model writing is good! It often has a sense of style & tone, variations in sentence structure & length, some great phrasing…

applicationsethan-mollick--x

I think frontier model writing is good! It often has a sense of style & tone, variations in sentence structure & length, some great phrasing, etc But it also has some weak spots (fiction!) & clear tic

IBM’s enterprise AI strategy makes trust and control the production test

Before artificial intelligence can scale, governed enterprise AI has to prove it can be trusted. As companies move from pilots to production, the real test is whether platforms can bring automation, t

applicationssiliconangle

Information Density as a Quantitative Measure for AI-enabled Virtual Sensing: Feasibility and Limits

arXiv:2605.08180v1 Announce Type: cross Abstract: Modern IoT and sensor networks generate vast amounts of data, posing significant challenges for storage, transmission, and real-time processing. Tradi

Information Filtering via Variational Regularization for Robot Manipulation

arXiv:2601.21926v4 Announce Type: replace Abstract: Diffusion-based visuomotor policies built on 3D visual representations have achieved strong performance in learning complex robotic skills. However,

Isomorphic Labs, an AI-powered drug discovery spinoff from Google DeepMind, raised 2.1B led by Thrive, after raising 600M in its first round in March 2025 (Pritam Biswas/Reuters)

Pritam Biswas / Reuters: Isomorphic Labs, an AI-powered drug discovery spinoff from Google DeepMind, raised 2.1B led by Thrive, after raising 600M in its first round in March 2025 — Isomorphic Labs, a

applicationstechmeme

JUST-DUB-IT: Video Dubbing via Joint Audio-Visual Diffusion

arXiv:2601.22143v2 Announce Type: replace-cross Abstract: Audio-Visual Foundation Models, which are pretrained to jointly generate sound and visual content, have recently shown an unprecedented abilit

Key Coverage Matters: Semi-Structured Extraction of OCR Clinical Reports

arXiv:2605.09440v1 Announce Type: cross Abstract: Clinical reports are often fragmented across healthcare institutions because privacy regulations and data silos limit direct information sharing. When

Kinematics-Driven Gaussian Shape Deformation for Blurry Monocular Dynamic Scenes

arXiv:2605.08635v1 Announce Type: new Abstract: Reconstructing dynamic 3D scenes from blurry monocular videos is challenging as motion-induced blur entangles object motion and geometry, hindering geom

LagrangianSplats: Divergence-Free Transport of Gaussian Primitives for Fluid Reconstruction

arXiv:2605.09299v1 Announce Type: cross Abstract: Reconstructing 3D fluid velocity fields from sparse 2D video observations is a highly ill-posed inverse problem, demanding both transport consistency

LeapTS: Rethinking Time Series Forecasting as Adaptive Multi-Horizon Scheduling

arXiv:2605.10292v1 Announce Type: cross Abstract: Time series forecasting serves as an essential tool for many real-world applications, supporting tasks such as resource optimization and decision-maki

Learning-Augmented Scalable Linear Assignment Problem Optimization via Neural Dual Warm-Starts

arXiv:2605.09382v1 Announce Type: cross Abstract: The Linear Assignment Problem (LAP) is a fundamental combinatorial optimization task with applications ranging from computer vision to logistics. Clas

LILO: Bayesian Optimization with Natural Language Feedback

arXiv:2510.17671v2 Announce Type: replace-cross Abstract: Many real-world optimization problems are guided by complex, subjective preferences that are difficult to express as explicit closed-form obje

LLARS: Enabling Domain Expert & Developer Collaboration for LLM Prompting, Generation and Evaluation

arXiv:2605.10593v1 Announce Type: new Abstract: We demonstrate LLARS (LLM Assisted Research System), an open-source platform that bridges the gap between domain experts and developers for building LLM

LLaVA-CKD: Bottom-Up Cascaded Knowledge Distillation for Vision-Language Models

arXiv:2605.10641v1 Announce Type: cross Abstract: Large Vision-Language Models (VLMs) are successful in addressing a multitude of vision-language understanding tasks, such as Visual Question Answering

LLM-guided Semi-Supervised Approaches for Social Media Crisis Data Classification

arXiv:2605.08448v1 Announce Type: new Abstract: Semi-supervised learning approaches have been investigated as a means to enhance the analysis of social media data in disaster management contexts. In t

MARGIN: Margin-Aware Regularized Geometry for Imbalanced Vulnerability Detection

arXiv:2605.10240v1 Announce Type: cross Abstract: Software vulnerability detection is critical for ensuring software security and reliability. Despite recent advances in deep learning, real-world vuln

Marrying Generative Model of Healthcare Events with Digital Twin of Social Determinants of Health for Disease Reasoning

arXiv:2605.09771v1 Announce Type: new Abstract: Despite the central role of sensor-derived measurements such as imaging traits and plasma biomarkers in biomedical research and clinical practice, exist

Medical Model Synthesis Architectures: A Case Study

arXiv:2605.09716v1 Announce Type: new Abstract: Medicine is rife with high-stakes uncertainty. Doctors routinely make clinical judgments and decisions that juggle many fundamental unknowns, like predi

Modular Retrieval-Augmented Generalization for Human Action Recognition

arXiv:2605.08117v1 Announce Type: cross Abstract: Inertial Measurement Unit (IMU)-based Human Activity Recognition (HAR) aims to interpret and classify user behaviors from temporal motion signals. Rec

Nectar: Neural Estimation of Cached-Token Attention via Regression

arXiv:2605.09778v1 Announce Type: cross Abstract: Evaluating softmax attention over a fixed long context requires reading every cached key-value pair for each new query token. For a given context (a b

applicationsarxiv-cs-cl

Neural Variance-aware Dueling Bandits with Deep Representation and Shallow Exploration

arXiv:2506.01250v2 Announce Type: replace Abstract: In this paper, we address the contextual dueling bandit problem by proposing variance-aware algorithms that leverage neural networks to approximate

NEXT: Multi-Grained Mixture of Experts via Text-Modulation for Multi-Modal Object Re-Identification

arXiv:2505.20001v5 Announce Type: replace Abstract: Multi-modal object Re-IDentification (ReID) aims to obtain complete identity features across heterogeneous modalities. However, most existing method

Noise-Started One-Step Real-World Super-Resolution via LR-Conditioned SplitMeanFlow and GAN Refinement

arXiv:2605.09328v1 Announce Type: new Abstract: Pre-trained text-to-image (T2I) diffusion models have shown strong potential for real-world image super-resolution (Real-ISR), owing to their noise-star

NoRIN: Backbone-Adaptive Reversible Normalization for Time-Series Forecasting

arXiv:2605.10823v1 Announce Type: new Abstract: Reversible instance normalization (RevIN) and its successors (Dish-TS, SAN, FAN) have become the de facto plug-in for time-series forecasting, yet the m

NoTVLA: Semantics-Preserving Robot Adaptation via Narrative Action Interfaces

arXiv:2510.03895v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models represent a pivotal advance in embodied intelligence, yet they confront critical barriers to real-world de

ObjView-Bench: Rethinking Difficulty and Deployment for Object-Centric View Planning

arXiv:2605.10707v1 Announce Type: new Abstract: Object-centric view planning is a core component of active geometric 3D reconstruction in robotics, yet existing evaluations often conflate object compl

On Observation Time for Recovering Latent Hawkes Networks

arXiv:2605.08400v1 Announce Type: cross Abstract: Dynamics of interacting systems in engineering, society, and nature often evolve over latent networks that govern which entities can interact. We stud

On the Overscaling Curse of Parallel Thinking: System Efficacy Contradicts Sample Efficiency

arXiv:2601.21619v2 Announce Type: replace-cross Abstract: Parallel thinking improves LLM reasoning through multi-path sampling and aggregation. In standard evaluations, due to a lack of sample-specifi

Online Sharp-Calibrated Bayesian Optimization

arXiv:2605.10572v1 Announce Type: new Abstract: Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box functions, commonly based on Gaussian process (GP) surrogate mo

Outlier-Robust Diffusion Solvers for Inverse Problems

arXiv:2605.09477v1 Announce Type: cross Abstract: Methods based on diffusion models (DMs) for solving inverse problems (IPs) have recently achieved remarkable performance. However, DM-based methods ty

PA-RNet: Perturbation-Aware Residual Network for Robust Multimodal Time Series Forecasting

arXiv:2508.04750v2 Announce Type: replace Abstract: In real-world applications, multimodal time-series forecasting faces a key challenge: textual information is often useful but unreliable. Auxiliary

PAINET: A Principled Efficient Transformer for 3D Dynamics Modeling

arXiv:2510.04233v2 Announce Type: replace-cross Abstract: Modeling 3D dynamics is a fundamental problem in multi-body systems across scientific and engineering domains and has important practical impl

PhysHanDI: Physics-Based Reconstruction of Hand-Deformable Object Interactions

arXiv:2605.09538v1 Announce Type: cross Abstract: While existing methods for reconstructing hand-object interactions have made impressive progress, they either focus on rigid or part-wise rigid object

PixelFlowCast: Latent-Free Precipitation Nowcasting via Pixel Mean Flows

arXiv:2605.10046v1 Announce Type: new Abstract: Precipitation nowcasting aims to forecast short-term radar echo sequences for extreme weather warning, where both prediction fidelity and inference effi

Playing Games with My Heart: An Evaluation of AI Companion Apps

arXiv:2605.08093v1 Announce Type: cross Abstract: The use of chatbots for various forms of companionship is growing rapidly, raising a myriad of questions about simulated relationships, emotional depe

Position: Avoid Overstretching LLMs for every Enterprise Task

arXiv:2605.09365v1 Announce Type: new Abstract: Enterprise workloads are dominated by deterministic, structured, and knowledge-dependent tasks operating under strict cost, latency, and reliability con

Prospective Compression in Human Abstraction Learning

arXiv:2605.09985v1 Announce Type: new Abstract: A core challenge in program synthesis is online library learning: the incremental acquisition of reusable abstractions under uncertainty about future ta

RAG-HAR: Retrieval Augmented Generation-based Human Activity Recognition

arXiv:2512.08984v2 Announce Type: replace-cross Abstract: Human Activity Recognition (HAR) underpins applications in healthcare, rehabilitation, fitness tracking, and smart environments, yet existing

Rethinking Evaluation of Multiple Sclerosis (MS) Lesion Segmentation Models

arXiv:2605.09666v1 Announce Type: cross Abstract: Multiple Sclerosis (MS) is a chronic autoimmune disease that can significantly reduce the quality of life of a patient. Existing treatment options can

Rethinking Gating Mechanism in Sparse MoE: Handling Arbitrary Modality Inputs with Confidence-Guided Gate

arXiv:2505.19525v3 Announce Type: replace-cross Abstract: Effectively managing missing modalities is a fundamental challenge in real-world multimodal learning scenarios, where data incompleteness ofte

RIR-Former: Coordinate-Guided Transformer for Continuous Reconstruction of Room Impulse Responses

arXiv:2602.01861v3 Announce Type: replace-cross Abstract: Room impulse responses (RIRs) are essential for many acoustic signal processing tasks, yet measuring them densely across space is often imprac

Root Cause Analysis of Measurement and Mechanistic Anomalies

arXiv:2601.23026v2 Announce Type: replace Abstract: Root cause analysis of anomalies aims to identify how and why a sample deviates from the normal process. Existing methods primarily focus on telling

RubiConv -- Efficient Boundary-Respecting Convolutions

arXiv:2605.08451v1 Announce Type: new Abstract: Convolutional architectures have emerged as powerful alternatives to Transformers for sequence modeling. The primary advantage is that they offer improv

SABER: A Scalable Action-Based Embodied Dataset for Real-World VLA Adaptation

arXiv:2605.09613v1 Announce Type: cross Abstract: Robotic deployment in real-world environments depends on rich, domain-specific action data as much as on strong model architecture. General-purpose ro

Scalable and Efficient Continual Learning from Demonstration via a Hypernetwork-generated Stable Dynamics Model

arXiv:2311.03600v3 Announce Type: replace Abstract: Robots capable of learning from demonstration (LfD) must exhibit stability while executing learned motion skills. To be effective in the real world,

Scalable Inspection Planning via Flow-based Mixed Integer Linear Programming

arXiv:2603.16593v2 Announce Type: replace Abstract: Inspection planning is concerned with computing the shortest robot path to inspect a given set of points of interest (POIs) using the robot's sensor

Shaping Schema via Language Representation as the Next Frontier for LLM Intelligence Expanding

arXiv:2605.09271v1 Announce Type: new Abstract: Although natural language is the default medium for Large Language Models (LLMs), its limited expressive capacity creates a profound bottleneck for comp