arXiv:2602.07303v2 Announce Type: replace-cross Abstract: Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions with clear boundaries, this structure is lost when stored as flat sequences. As a result, state-of-the-art methods often miss true dependencies within executions while learning spurious correlations across unrelated events. We […]
ZeroFold: Protein-RNA Binding Affinity Predictions from Pre-Structural Embeddings
arXiv:2603.23583v1 Announce Type: new Abstract: The accurate prediction of protein-RNA binding affinity remains an unsolved problem in structural biology, limiting opportunities in understanding gene regulation and designing RNA-targeting therapeutics. A central obstacle is the structural flexibility of RNA, as, unlike proteins, RNA molecules exist as dynamic conformational ensembles. Thus, committing to a single predicted structure […]
DVM: Real-Time Kernel Generation for Dynamic AI Models
arXiv:2603.24239v1 Announce Type: cross Abstract: Dynamism is common in AI computation, e.g., the dynamic tensor shapes and the dynamic control flows in models. Due to the long compilation time, existing runtime compilation damages the model efficiency, while the offline compilers either suffer from the long compilation time and device memory footprint to cover all the […]
Counting Without Numbers & Finding Without Words
arXiv:2603.24470v1 Announce Type: cross Abstract: Every year, 10 million pets enter shelters, separated from their families. Despite desperate searches by both guardians and lost animals, 70% never reunite, not because matches do not exist, but because current systems look only at appearance, while animals recognize each other through sound. We ask, why does computer vision […]
Evolutionarily Stable Stackelberg Equilibrium
arXiv:2603.18385v2 Announce Type: replace-cross Abstract: We present a new solution concept called evolutionarily stable Stackelberg equilibrium (SESS). We study the Stackelberg evolutionary game setting in which there is a single leading player and a symmetric population of followers. The leader selects an optimal mixed strategy, anticipating that the follower population plays an evolutionarily stable strategy […]
UNGT: Ultrasound Nasogastric Tube Dataset for Medical Image Analysis
arXiv:2502.14915v2 Announce Type: replace Abstract: We develop a novel ultrasound nasogastric tube (UNGT) dataset to address the lack of public nasogastric tube datasets. The UNGT dataset includes 493 images gathered from 110 patients with an average image resolution of approximately 879 $times$ 583. Four structures, encompassing the liver, stomach, tube, and pancreas, are precisely annotated. […]
Environment-Grounded Multi-Agent Workflow for Autonomous Penetration Testing
arXiv:2603.24221v1 Announce Type: cross Abstract: The increasing complexity and interconnectivity of digital infrastructures make scalable and reliable security assessment methods essential. Robotic systems represent a particularly important class of operational technology, as modern robots are highly networked cyber-physical systems deployed in domains such as industrial automation, logistics, and autonomous services. This paper explores the use […]
CIRCLE: A Framework for Evaluating AI from a Real-World Lens
arXiv:2602.24055v4 Announce Type: replace Abstract: This paper proposes CIRCLE, a six-stage, lifecycle-based framework to bridge the reality gap between model-centric performance metrics and AI’s materialized outcomes in deployment. Current approaches such as MLOps frameworks and AI model benchmarks offer detailed insights into system stability and model capabilities, but they do not provide decision-makers outside the […]
100x Cost & Latency Reduction: Performance Analysis of AI Query Approximation using Lightweight Proxy Models
arXiv:2603.15970v3 Announce Type: replace-cross Abstract: Several data warehouse and database providers have recently introduced extensions to SQL called AI Queries, enabling users to specify functions and conditions in SQL that are evaluated by LLMs, thereby broadening significantly the kinds of queries one can express over the combination of structured and unstructured data. LLMs offer remarkable […]
Proximity Matters: Local Proximity Enhanced Balancing for Treatment Effect Estimation
arXiv:2407.01111v2 Announce Type: replace-cross Abstract: Heterogeneous treatment effect (HTE) estimation from observational data poses significant challenges due to treatment selection bias. Existing methods address this bias by minimizing distribution discrepancies between treatment groups in latent space, focusing on global alignment. However, the fruitful aspect of local proximity, where similar units exhibit similar outcomes, is often […]
Who Benefits from RAG? The Role of Exposure, Utility and Attribution Bias
arXiv:2603.24218v1 Announce Type: cross Abstract: Large Language Models (LLMs) enhanced with Retrieval-Augmented Generation (RAG) have achieved substantial improvements in accuracy by grounding their responses in external documents that are relevant to the user’s query. However, relatively little work has investigated the impact of RAG in terms of fairness. Particularly, it is not yet known if […]
PromptLoop: Plug-and-Play Prompt Refinement via Latent Feedback for Diffusion Model Alignment
arXiv:2510.00430v2 Announce Type: replace-cross Abstract: Despite recent progress, reinforcement learning (RL)-based fine-tuning of diffusion models often struggles with generalization, composability, and robustness against reward hacking. Recent studies have explored prompt refinement as a modular alternative, but most adopt a feed-forward approach that applies a single refined prompt throughout the entire sampling trajectory, thereby failing to […]