Knowledge catalogue
arXiv:2608.30130v1 Announce Type: cross Abstract: Retrieval-augmented language models can fail to respect negative constraints when the retriever supplies evidence about concepts the user explicitly e
arXiv:2608.30893v1 Announce Type: new Abstract: Electrocardiogram (ECG) interpretation requires knowledge of cardiology, electrophysiology, clinical diagnosis, ECG waveforms, signal acquisition, and i
arXiv:2608.28968v1 Announce Type: new Abstract: Semantic Search on LinkedIn must retrieve relevant profiles from a corpus of hundreds of millions in response to natural-language queries such as 'a fin
arXiv:2608.29118v1 Announce Type: new Abstract: Fine-tuning large language models (LLMs) on narrowly harmful datasets can lead to misalignment broadly, a phenomenon known as emergent misalignment (EM)
arXiv:2608.30462v1 Announce Type: cross Abstract: Large language models exhibit substantial performance variation across languages, even when solving semantically equivalent tasks. Existing analyses o
arXiv:2608.30261v1 Announce Type: cross Abstract: We estimate the conditional population-risk curve of a realized smooth nonconvex gradient flow from the training sample. Flow approximate leave-one-ou
arXiv:2608.31066v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning improves multi-step problem solving, but long reasoning traces inflate inference cost. Token-level CoT compression redu
arXiv:2608.29348v1 Announce Type: new Abstract: Background: Patient details and acquisition metadata are important for clinical decisions, image quality control, and automated research pipelines, but
arXiv:2506.15626v3 Announce Type: replace-cross Abstract: extbf{Objective:} Brain-predicted age difference (BrainAGE) is a neuroimaging biomarker reflecting brain health. However, training robust Brai
arXiv:2608.29802v1 Announce Type: new Abstract: Face recognition systems are increasingly deployed in security-critical applications, yet they remain vulnerable to presentation and morph attacks. Pres
arXiv:2608.28594v1 Announce Type: new Abstract: Conversational analytics systems assume the user already has a well-formed question, leaving a non-expert facing a blank query box on an unfamiliar ente
arXiv:2608.30425v1 Announce Type: new Abstract: Cross-lingual aspect-based sentiment analysis (ABSA) transfers knowledge from a source language with annotated data to a target language, enabling fine-
arXiv:2608.30103v1 Announce Type: cross Abstract: Bilevel mixed-integer linear optimization problems model hierarchical decision processes in which a leader anticipates the optimal response of a follo
arXiv:2608.29251v1 Announce Type: new Abstract: Privacy protection for live web traffic requires more than detecting private spans. Agent-based privacy protection systems must determine whether an out
arXiv:2608.30841v1 Announce Type: new Abstract: Large language models can often generate plausible mathematical reasoning traces, but reliably identifying the correct solution among multiple candidate
arXiv:2608.31053v1 Announce Type: new Abstract: Diffusion models have achieved strong results in high-fidelity image synthesis, but their iterative sampling process makes large-scale generation comput
arXiv:2608.29783v1 Announce Type: new Abstract: Industrial anomaly detection is a critical component of modern manufacturing. Most traditional unsupervised methods rely on modelling normal feature dis
arXiv:2608.28602v1 Announce Type: new Abstract: Parkinson disease PD is a progressive neurodegenerative disease that can have a significant impact on motor performance resulting in the appearance of s
arXiv:2604.02382v2 Announce Type: replace-cross Abstract: The scale and complexity of modern cloud infrastructure have made 'Infrastructure-as-Code' (IaC) essential for managing deployments through de
arXiv:2608.29901v1 Announce Type: cross Abstract: Electronic Health Record (EHR) prediction models in the intensive care unit must learn from sparse and irregular measurements while preserving the cli
arXiv:2608.29455v1 Announce Type: new Abstract: LLMs are increasingly used as human surrogates, often on the premise that richer persona data could make them substitutes or exploratory tools for speci
arXiv:2608.29616v1 Announce Type: new Abstract: Criminal judgment prediction requires models to infer statutory articles, charges, and sentencing outcomes from case facts. Unlike standard classificati
arXiv:2508.15757v2 Announce Type: replace Abstract: Configuration optimization remains a critical bottleneck in machine learning, requiring coordinated tuning across model architecture, training strat
arXiv:2608.30303v1 Announce Type: new Abstract: Search agents reduce hallucination by grounding answers in retrieved web evidence. Yet reliance on retrieval also creates an attack surface: poisoned co
arXiv:2608.30679v1 Announce Type: cross Abstract: Large Reasoning Models produce Long Chains-of-Thought (LCoTs) which involve breaking down the problem into smaller reasoning steps before reaching the
arXiv:2608.29494v1 Announce Type: new Abstract: Much of human health and function unfolds beyond the clinic, through the movements of everyday life. Wrist-worn accelerometers capture these movements c
arXiv:2412.15957v2 Announce Type: replace-cross Abstract: The rapid development of large language models (LLMs) has transformed many industries, including healthcare. In practice, hospitals and patien
arXiv:2608.29305v1 Announce Type: cross Abstract: Large language model (LLM) agents have demonstrated remarkable proficiency in manually constructed environments, yet their performance frequently coll
arXiv:2608.28601v1 Announce Type: new Abstract: Interactive visualizations support conceptual understanding in undergraduate mathematics, but building them has required programming expertise most inst
arXiv:2608.29357v1 Announce Type: new Abstract: Multimodal search agents answer visual questions by interleaving image understanding, web retrieval, tool use, and evidence synthesis. Strong systems ex
arXiv:2608.31102v1 Announce Type: cross Abstract: Industrial post-training is a brownfield regime. Teams inherit a deployed checkpoint and must land targeted improvements under fixed compute and mixtu
arXiv:2608.27580v2 Announce Type: replace Abstract: Safety guardrails serve as the last line of defense against harmful inputs and outputs of large language models (LLMs), yet they are trained and eva
arXiv:2608.28624v1 Announce Type: cross Abstract: Accurate interpretation of single-visit and longitudinal clinical assessments for Parkinson's disease is time-consuming and often depends on specialis
arXiv:2509.04183v3 Announce Type: replace-cross Abstract: The growing demand for scalable psychological counseling highlights the need for high-quality, privacy-compliant data, yet such data remains s
arXiv:2608.30371v1 Announce Type: new Abstract: Automatic cardiac image segmentation is pivotal for diagnosing and treating cardiac diseases. In this work, we introduce MCSeg, a volumetric transformer
arXiv:2607.14252v2 Announce Type: replace-cross Abstract: Embodied agents accumulate experience over time. We study how accumulated experience can be formed into persistent memory for future reasoning
arXiv:2608.29617v1 Announce Type: cross Abstract: This paper introduces a hybrid fact-checking framework that integrates Knowledge Graph-based semantic memory with adversarial multi-agent reasoning fo
arXiv:2603.21716v2 Announce Type: replace-cross Abstract: Efficient selection among multiple generative models is increasingly important in modern generative AI, where sampling from suboptimal models
arXiv:2608.30463v1 Announce Type: new Abstract: Solvability detection is one of the most challenging aspects of mathematical reasoning for Large Language Models (LLMs). While prior work has studied th
arXiv:2507.23129v2 Announce Type: replace-cross Abstract: We preseent an open-source image reconstruction package built upon PyTorch, enabling modern deep-learning reconstructions. It uses open data f
arXiv:2608.28680v1 Announce Type: new Abstract: Informal settlements represent a major urban challenge in rapidly expanding cities, yet their identification from Earth Observation (EO) data remains di
arXiv:2608.29008v1 Announce Type: new Abstract: Accurate forecasting of grape berry temperature (Tb) is essential for enabling timely heat stress management in vineyards. In this study, a feed-forward
arXiv:2608.29540v1 Announce Type: new Abstract: This paper introduces NepScript Genesis, a Neural Architecture Search (NAS) framework for automated Generative Adversarial Network (GAN) discovery, appl
arXiv:2608.29609v1 Announce Type: new Abstract: Semantic segmentation is a crucial task for understanding Mars, the most Earth-like planet in our solar system. However, it is challenging because the M
arXiv:2601.15436v3 Announce Type: replace Abstract: We propose a novel perspective for probing LLM sycophancy in a direct and neutral way, mitigating various forms of uncontrolled bias, noise, or mani
arXiv:2608.29944v1 Announce Type: new Abstract: Brain tumor segmentation in magnetic resonance imaging (MRI) is a critical task for diagnosis and treatment planning. Despite the success of deep learni
arXiv:2608.31017v1 Announce Type: cross Abstract: Ambient AI scribes draft clinical notes under the reassurance that a clinician signs every note. We audited three commercial AI scribes on the same 14
arXiv:2608.30241v1 Announce Type: new Abstract: Recent efforts have aimed to automate scientific diagram generation from paper content (Lin et al., 2026; Zhu et al., 2026a). However, fully satisfying
arXiv:2608.28633v1 Announce Type: cross Abstract: Generative AI systems increasingly mediate cultural adaptation, but their cultural decisions are often hidden inside prompts, transient model plans, o
arXiv:2608.28754v1 Announce Type: cross Abstract: This article introduces peer k-oversight, a property of sequential collective decision mechanisms requiring at least k agents to be responsible for ev
arXiv:2608.28728v1 Announce Type: new Abstract: Urban construction governance requires early decisions that connect workplace safety, permitting requirements, and community impact, yet the relevant ev
arXiv:2603.03485v4 Announce Type: replace-cross Abstract: Recent video diffusion models have achieved impressive capabilities as large-scale generative world models. However, these models often strugg
arXiv:2608.28891v1 Announce Type: new Abstract: Pixel-level cross-view geo-registration aims to align a query image (e.g., drone) to a geo-referenced satellite map so that every query pixel can be map
arXiv:2608.28640v1 Announce Type: cross Abstract: In this paper, we present PromptKWS, a novel Prompt-guided keyword spotting (KWS) framework to improve the accuracy of open vocabulary KWS systems. In
arXiv:2608.30229v1 Announce Type: new Abstract: Korean introduces an additional typographical perturbation level not captured by ordinary character-level edit models: because syllable blocks are inter
arXiv:2608.30633v1 Announce Type: new Abstract: Timely post-disaster building damage assessment from satellite imagery is a critical engineering decision support task, yet it remains constrained by cl
arXiv:2608.30041v1 Announce Type: cross Abstract: Large language model agents place outputs from external skills into their execution context, allowing attacker-controlled data to influence later priv
arXiv:2608.30609v1 Announce Type: cross Abstract: Large language models are increasingly capable in general, but their utility can remain modest in niche or understudied areas. One approach to address
arXiv:2601.13206v2 Announce Type: replace Abstract: Large Language Models (LLMs) generate text token-by-token in discrete time, yet real-world communication, from therapy sessions to business negotiat
arXiv:2608.28656v1 Announce Type: cross Abstract: Behavior-cloned Vision-Language-Action (VLA) driving policies struggle with rare rule-governed maneuvers at signalized intersections. Braking and laun