Search: “applications”

When unlearning is free: leveraging low influence points to reduce computational costs

arXiv:2512.05254v2 Announce Type: replace Abstract: As concerns around data privacy in machine learning grow, the ability to unlearn, or remove, specific data points from trained models becomes increa

31 Jul 2026

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Applications

WIDE: Boosting Adaptive LLM Inference via Token-level Dynamic Width Pruning

DGX agent

arXiv:2607.28418v1 Announce Type: cross Abstract: Pruning is a promising approach for improving the efficiency of LLMs. Existing static structured pruning methods are hardware-friendly and can deliver

applicationsarxiv-cs-cl

31 Jul 2026

ZAPs: A Reward Attribution Framework for DeFi Ecosystems with Adversarial-Robust Scoring via Parallel Anomaly Ensemble Detection

arXiv:2607.27859v1 Announce Type: cross Abstract: Incentive programs are central to user acquisition in decentralized finance, but many reward systems rely on raw volume, transaction count, and wallet

31 Jul 2026

Actions Have Consequences: Detecting Outcome Performativity using Intervention Testing

arXiv:2607.26908v1 Announce Type: new Abstract: In many domains such as Palliative Care, Credit Assignment and Recommender Systems, predictions may causally influence the outcomes they predict. This p

Answer from OpenAI

applicationsethan-mollick--x

Answer from OpenAI @emollick re ARC-AGI-3: human testers scored ~48% (ARC uploaded testers logs to HuggingFace some time ago, I believe). re GDPval: it’s close to saturated now, so we’re mostly lookin

Automated Multilabel Mpox Research Classification with Explainable Transformer Models

arXiv:2607.26700v1 Announce Type: new Abstract: The Mpox outbreak remains a serious public health issue, with the WHO (World Health Organization) reporting increasing cases in some regions. Research o

Big unsaturated benchmarks that have this: ARC-AGI, the original GDPval (not GDPval-AA), METR long horizons, ASI cyber tasks, (Speaking of w…

applicationsethan-mollick--x

Ethan Mollick highlights that large, currently under‑explored benchmarks (e.g., ARC‑AGI, GDPval, METR long horizons, ASI cyber tasks) are growing in complexity, yet they increasingly lack systematic h

ClockRoPE: Random Fourier Rotations for Temporal Routine Modeling

arXiv:2607.26369v1 Announce Type: new Abstract: Rotary Position Embedding (RoPE) has been widely adopted in transformer-based large language models. However, its log-linear frequency schedule, origina

ContactFlow: A video action conditioning that transfers across embodiments

arXiv:2607.26579v1 Announce Type: cross Abstract: World models offer a promising route toward robot planning by enabling agents to imagine and verify the consequences of actions before execution. Howe

Early Failure Prediction from Near-Anomaly Detection: A Proactive Approach

arXiv:2607.26704v1 Announce Type: cross Abstract: Anomaly detection methods often have uncertain behavior with respect to samples near the distribution boundary, limiting their ability to anticipate f

GroupRAG: Cognitively Inspired Group-Aware Retrieval and Reasoning via Knowledge-Driven Problem Structuring

arXiv:2603.26807v2 Announce Type: replace-cross Abstract: The performance of language models is commonly limited by insufficient knowledge and constrained reasoning. Prior approaches such as Retrieval

HealthSLM-Bench: Benchmarking Small Language Models for Mobile and Wearable Healthcare Monitoring

arXiv:2509.07260v5 Announce Type: replace-cross Abstract: Mobile and wearable healthcare monitoring play a vital role in facilitating timely interventions, managing chronic health conditions, and ulti

I’m excited to share my next chapter: I’ve joined @FireworksAI_HQ . From AMD, Apple, Uber, Meta, Google, and most recently Snowflake, I’ve w…

applicationsfireworks-ai--x

I’m excited to share my next chapter: I’ve joined @FireworksAI_HQ . From AMD, Apple, Uber, Meta, Google, and most recently Snowflake, I’ve worked on many of the foundational technologies that power mo

Kairos: Numerically Robust News Recommendation under Item Cold-Start via Cholesky-based LinUCB

arXiv:2607.26832v1 Announce Type: new Abstract: Algorithmic news personalization in regional markets often fails because modern deep learning models require massive interaction data while real-world n

LAMUS: A Large-Scale Corpus for Legal Argument Mining from U.S. Caselaw using LLMs

arXiv:2603.08286v2 Announce Type: replace Abstract: Legal argument mining aims to identify and classify the functional components of judicial reasoning, such as facts, issues, rules, analysis, and con

Making Implicit Premises Explicit in Logical Understanding of Enthymemes

arXiv:2603.06114v2 Announce Type: replace Abstract: Real-world arguments in text and dialogues are normally enthymemes (i.e. some of their premises and/or claims are implicit). Natural language proces

MLVC: Multi-platform Learned Video Codec for Real-World Deployment [P]

applicationsr-machinelearning

I've always found it a little strange that AI is everywhere, but the codecs we use in practice are the traditional hand-engineered systems like h.264, h.265, av1. Alexnet started the wave of neural ne

RVC-NMPC: Nonlinear Model Predictive Control with Reciprocal Velocity Constraints for Mutual Collision Avoidance in Agile UAV Flight

arXiv:2512.08574v2 Announce Type: replace Abstract: This paper presents an approach to mutual collision avoidance based on Nonlinear Model Predictive Control (NMPC) with time-dependent Reciprocal Velo

ScalablePromptus: Scalable and High-Fidelity Prompt-Based Video Streaming

arXiv:2607.26106v1 Announce Type: cross Abstract: Prompt-based video streaming transmits compact semantic prompts instead of pixel-level content for generative reconstruction, enabling ultra-low-bitra

See2Think: Do Multimodal Models Really Use Intermediate Visual States?

arXiv:2607.26769v1 Announce Type: new Abstract: Multimodal large language models increasingly use sketches, annotations, tools, and intermediate images during reasoning, but it remains unclear whether

Simplex Demixing: Disentangling Multiple Light-Flavor Jets at Colliders

arXiv:2607.24921v1 Announce Type: cross Abstract: Providing a practical and hadron-level definition of multiple jet flavors has been a long-standing challenge in collider physics. Previous work has in

Single-Beat Cuffless Blood Pressure Estimation Using Ear-PPG and ECG with a Lightweight Hybrid Learning Framework

arXiv:2607.27076v1 Announce Type: new Abstract: Continuous cuffless blood pressure (BP) monitoring remains challenging due to motion artifacts, physiological variability, and the limited robustness of

Speech2Grasp: Data-Efficient Transfer of Text-Conditioned Grasp Detection to Speech in Humanoid Robots

arXiv:2607.26567v1 Announce Type: cross Abstract: Humanoid robots increasingly require multi-modal understanding for natural interaction with humans. Despite the prominence of vision-language models,

Starting in 15 minutes

applicationstogether-ai--x

Starting in 15 minutes Kimi K3 has everyone’s attention. On July 30, hear @Kimi_Moonshot's Feihu Tang explain the architecture and decisions behind it. He joins Jue Wang and Zain Hasan from Together A

Task and Skill Planning: Hierarchical Robot Planning with Black-Box Skills

arXiv:2504.17901v3 Announce Type: replace Abstract: Task and motion planning (TAMP) is a well-established approach for solving long-horizon robot planning problems. Although TAMP methods have historic

The Rise of AI in Weather and Climate Information and its Impact on Global Inequality

arXiv:2603.05710v2 Announce Type: replace-cross Abstract: AI development's current trajectory risks automating and amplifying the North-South divide in the global climate information system. Frontier

Research

Using large language models to probe the limits of atom-centered structural descriptors

arXiv:2607.26984v1 Announce Type: cross Abstract: Mapping an atomic structure to a compact set of geometric descriptors is an essential step in any machine-learning application to atomic-scale modelin

researcharxiv-cs-lg

Voronoi Histograms for Adaptive Vectorization of Expected Persistence Diagrams

arXiv:2607.27126v1 Announce Type: new Abstract: Persistence Diagram (PD) is known to capture point cloud topology effectively, but its computation has high time complexity. Expected Persistence Diagra

When Do Learned Diffusion Proposals Help Constraint Solving? A Controlled Study on Continuous Algebraic Systems

arXiv:2607.27169v1 Announce Type: new Abstract: Solving a continuous algebraic constraint system requires two decisions: which values satisfy the constraints, and which structural augmentation renders

A Machine-Learning-Based Gas Lift Optimization Workflow for Unconventional Fields

arXiv:2607.25885v1 Announce Type: cross Abstract: In this paper, we present an automated data-driven workflow using Machine Learning (ML) for gas lift optimization in unconventional fields. This workf

A2TTA: Anchored-and-Agile Test-Time Adaptation for Evolving Traffic Sensor Networks

arXiv:2607.25875v1 Announce Type: cross Abstract: Traffic forecasting is important for efficient traffic management and route planning in smart cities. Existing traffic forecasting studies typically a

AngelSpec: Towards Real-World High Performance Inference with Speculative Decoding

arXiv:2607.25852v1 Announce Type: new Abstract: Speculative decoding accelerates large language model inference without changing the target distribution, but no single drafting structure performs best

Belief-Aware Influence and Trust (BAIT): Shaping Human Belief During Repeated Human-Robot Interaction

arXiv:2607.25327v1 Announce Type: new Abstract: Repeated human-robot interaction (HRI) requires proactively accounting for humans who continually adapt to evolving beliefs about the robot. Prior frame

Can Deep Generative Models Reproduce Non-Stationary Gaussian Random Fields?

arXiv:2607.25929v1 Announce Type: cross Abstract: Deep generative models (DGMs) are widely used for complex high-dimensional data and increasingly applied to spatial and spatio-temporal modeling. Thei

Cerebras and AMD partner to build the world’s fastest disaggregated AI inference solution

Disaggregated AI inference is proving to be more than a complementary answer to the prefill and decode bottleneck slowing enterprise AI at scale, and Cerebras and AMD just announced a partnership to b

applicationssiliconangle

Characterizing and Mitigating the Effects of Device Temperature on RF Fingerprinting Accuracy

arXiv:2607.25070v1 Announce Type: cross Abstract: Radio Frequency Fingerprinting (RFFP) has emerged as a promising approach for device authentication by exploiting hardware-specific impairments embedd

CHARM: A Multimodal Graph Foundation Model with Hierarchical Context Modeling for Zero-Shot Transfer

arXiv:2607.26023v1 Announce Type: new Abstract: Graph foundation models (GFMs) have emerged as a promising paradigm for transferring knowledge across graph domains and tasks. Real-world graphs associa

Computational Extraction of Legal Causes via al-Sabr wa al-Taqsim: A Set-Theoretic Formalization for Closed Fiqh Chapters

arXiv:2607.25605v1 Announce Type: new Abstract: This paper presents a set-theoretic formalization of the classical usuli method of al-Sabr wa al-Taqsim (Examination and Division) for extracting legal

Decompose and Reorganize: Planning with Primitives and Visuomotor Policies Learned from Demonstrations

arXiv:2607.25397v1 Announce Type: new Abstract: Successfully automating dexterous, long-horizon robotic manipulation requires frameworks capable of both high-level reasoning and fine-grained execution

Depth to Anatomy: Organ Localization from Depth Images for Automated Patient Table Positioning in Radiology Workflow

arXiv:2601.18260v3 Announce Type: replace Abstract: In clinical radiology, accurate patient table positioning is essential to align specific internal organs of interest with the scanner imaging isocen

Detecting CSAM Text-to-Image LoRAs From Weights

arXiv:2607.25750v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) fine-tuning has made it cheap and easy to customize open-weight image generation models for specific tasks, including the pro

DSevolve: Enabling Real-Time Adaptive Scheduling on Dynamic Flexible Job Shop with LLM-Evolved Heuristic Portfolios

arXiv:2603.27628v2 Announce Type: replace Abstract: In dynamic flexible job shops, order arrivals, machine breakdowns, and processing-time deviations continually reshape the scheduling state and the p

Dynamic Multi-Criteria Bottleneck Severity Index (DMBSI) for Semiconductor Wafer Manufacturing: A Genetically Optimised Framework for Reentrant Production Systems

arXiv:2607.24819v1 Announce Type: cross Abstract: Wafer fabrication exhibits unique characteristics, including reentrant process flows, variable bottlenecks, and highly variable process conditions. In

Eliminating Propagation Delay: Attention-Based Spatial-Temporal Fusion Graph Convolution Network for Traffic Flow Prediction

arXiv:2607.24885v1 Announce Type: cross Abstract: Predicting traffic flow is crucial to optimizing transportation systems and improving urban mobility. Many graph convolution-based models have been pr

Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models

arXiv:2607.26000v1 Announce Type: cross Abstract: Tabular Foundation Models (TFMs) have emerged as novel approaches for tabular predictive tasks, demonstrating competitive predictive performance to en

Enabling Fully Integer-Only Inference for Lightweight Detection Transformers

arXiv:2607.24981v1 Announce Type: new Abstract: Vision Transformer detectors now approach the accuracy of CNNs but remain difficult to deploy on NPUs and microcontrollers because key components, inclu

Explainable AI for Chronic Kidney Disease Prediction Using Simulated Federated Learning

arXiv:2607.25348v1 Announce Type: cross Abstract: Chronic Kidney Disease (CKD), characterized by the gradual loss of kidney function, remains a significant public health challenge. Early detection is

Extreme Event Aware (eta-) Learning

arXiv:2510.19161v2 Announce Type: replace-cross Abstract: Quantifying and predicting rare and extreme events is challenging because such events are infrequent, severe, and expensive to simulate. Exist