Knowledge catalogue
arXiv:2508.07112v4 Announce Type: replace-cross Abstract: Lifting-based 3D human pose estimation infers 3D joints from 2D keypoints but generalizes poorly because (x,y) coordinates alone are an ill-
arXiv:2604.06231v1 Announce Type: cross Abstract: Database systems incorporate an ever-growing number of functions in their kernels (a.k.a., database native functions) for scenarios like new applicati
arXiv:2505.20662v3 Announce Type: replace Abstract: Efficient reproduction of research papers is pivotal to accelerating scientific progress. However, the increasing complexity of proposed methods oft
arXiv:2604.07041v1 Announce Type: cross Abstract: Text-to-SQL is the task of translating natural language queries into executable SQL for a given database, enabling non-expert users to access structur
arXiv:2604.08540v1 Announce Type: cross Abstract: Text-to-Audio-Video (T2AV) generation is rapidly becoming a core interface for media creation, yet its evaluation remains fragmented. Existing benchma
arXiv:2510.21366v3 Announce Type: replace Abstract: In this work, we propose a novel framework to enable diffusion models to adapt their generation quality based on real-time network bandwidth constra
arXiv:2601.15474v2 Announce Type: replace-cross Abstract: Graph neural network (GNN) have demonstrated exceptional performance in solving critical problems across diverse domains yet remain susceptibl
arXiv:2604.08138v1 Announce Type: new Abstract: A join is a set of manuscript fragments identified as originally emanating from the same manuscript. We study manuscript join retrieval: Given a query i
arXiv:2509.23310v3 Announce Type: replace Abstract: Deep learning-based techniques for the analysis of multimodal remote sensing data have become popular due to their ability to effectively integrate
arXiv:2510.03046v2 Announce Type: replace Abstract: Machine learning potentials (MLPs) have become essential for large-scale atomistic simulations, enabling ab initio-level accuracy with computational
arXiv:2604.06405v1 Announce Type: new Abstract: Data harmonization remains a major bottleneck for integrative analysis due to heterogeneity in schemas, value representations, and domain-specific conve
arXiv:2508.04691v2 Announce Type: replace-cross Abstract: As humans move toward collaborating with coordinated robot teams, understanding how these teams coordinate and fail is essential for building
arXiv:2601.05529v5 Announce Type: replace Abstract: High success rates on navigation-related tasks do not necessarily translate into reliable decision making by foundation models. To examine this gap,
arXiv:2604.08260v1 Announce Type: new Abstract: Knowledge Tracing (KT) aims to predict learners' future performance from past interactions. While recent KT approaches have improved via learning item r
arXiv:2603.18019v2 Announce Type: replace Abstract: Do language model benchmarks actually measure what practitioners intend them to ? High-level metadata is too coarse to convey the granular reality o
arXiv:2604.06185v1 Announce Type: cross Abstract: Fulfilling user needs through Large Language Model multi-turn, multi-step tool-use is rarely a straightforward process. Real user interactions are inh
arXiv:2604.06674v1 Announce Type: cross Abstract: Meaning in Persian poetry is both historical and relational. Words persist through literary tradition while shifting their force through changing cons
arXiv:2604.06173v1 Announce Type: cross Abstract: Legal QA benchmarks have predominantly focused on case law, overlooking the unique challenges of statute-centric regulatory reasoning. In statutory do
arXiv:2604.06201v1 Announce Type: cross Abstract: While most reading comprehension benchmarks for LLMs focus on factual information that can be answered by localizing specific textual evidence, many r
arXiv:2604.06373v1 Announce Type: cross Abstract: New generation of AI coding tools, including AI-powered IDEs equipped with agentic capabilities, can generate code within the context of the project.
arXiv:2604.07306v1 Announce Type: cross Abstract: Existing dynamic data pruning methods often fail under noisy-label settings, as they typically rely on per-sample loss as the ranking criterion. This
arXiv:2604.08038v1 Announce Type: new Abstract: In a real-world traffic scenario, varying-scale objects are usually distributed in a cluttered background, which poses great challenges to accurate dete
arXiv:2604.07740v1 Announce Type: new Abstract: In recent years, video-based person Re-Identification (ReID) has gained attention for its ability to leverage spatiotemporal cues to match individuals a
arXiv:2604.06738v1 Announce Type: cross Abstract: We study offline learning in KL-regularized two-player zero-sum games, where policies are optimized under a KL constraint to a fixed reference policy.
arXiv:2604.07749v1 Announce Type: new Abstract: Large language models (LLMs) can shift their answers under pressure in ways that reflect accommodation rather than reasoning. Prior work on sycophancy h
arXiv:2604.07763v1 Announce Type: new Abstract: As generative artificial intelligence evolves, deepfake attacks have escalated from single-modality manipulations to complex, multimodal threats. Existi
arXiv:2604.06820v1 Announce Type: new Abstract: Large language models (LLMs) can generate persuasive narratives at scale, raising concerns about their potential use in disinformation campaigns. Assess
arXiv:2604.07198v1 Announce Type: new Abstract: Emotion annotation is inherently subjective and cognitively demanding, producing signals that reflect diverse perceptions across annotators rather than
arXiv:2604.06727v1 Announce Type: new Abstract: Heterogeneity in time series data is more pronounced than in vision or language, as temporal dynamics vary substantially across domains and tasks. Exist
arXiv:2604.06349v1 Announce Type: cross Abstract: Generalizing from a single labeled source domain to unseen target domains, without access to any target data during training, remains a fundamental ch
arXiv:2604.06701v1 Announce Type: new Abstract: Autoencoders are widely used for dimensionality reduction, based on the assumption that high-dimensional data lies on low-dimensional manifolds. Regular
arXiv:2604.08111v1 Announce Type: cross Abstract: Machine unlearning enables models to selectively forget training data, driven by privacy regulations such as GDPR and CCPA. However, its fairness impl
arXiv:2604.07677v1 Announce Type: new Abstract: Spatial single-loop mechanisms such as Bennett linkages offer a unique combination of one-degree-of-freedom actuation and nontrivial spatial trajectorie
arXiv:2604.06336v1 Announce Type: cross Abstract: Graph Transformers have recently attracted attention for molecular property prediction by combining the inductive biases of graph neural networks (GNN
arXiv:2604.08410v1 Announce Type: new Abstract: In unstructured environments, functional dexterous grasping calls for the tight integration of semantic understanding, precise 3D functional localizatio
arXiv:2604.06216v1 Announce Type: cross Abstract: As LLM-powered chatbots are increasingly deployed in mental health services, detecting hallucinations and omissions has become critical for user safet
arXiv:2604.06233v1 Announce Type: new Abstract: Safety-trained language models routinely refuse requests for help circumventing rules. But not all rules deserve compliance. When users ask for help eva
arXiv:2604.06323v2 Announce Type: cross Abstract: Blockchain and artificial intelligence (AI) are increasingly proposed together for securing intelligent networks, but the literature remains fragmente
arXiv:2604.07606v1 Announce Type: new Abstract: AI-driven sign language interpretation is limited by a lack of high-quality annotated data. New datasets including ASL STEM Wiki and FLEURS-ASL contain
arXiv:2604.08068v1 Announce Type: new Abstract: Decoding visual information from electroencephalography (EEG) has recently achieved promising results, primarily focusing on reconstructing two-dimensio
arXiv:2601.02670v2 Announce Type: replace Abstract: We introduce self-jailbreaking, a threat model in which an aligned LLM guides its own compromise. Unlike most jailbreak techniques, which oft
arXiv:2604.07154v1 Announce Type: cross Abstract: Multimodal imaging analysis often relies on joint latent representations, yet these approaches rarely define what information is shared versus modalit
arXiv:2604.05429v2 Announce Type: replace-cross Abstract: Addressing the critical need for intelligent, context-aware energy management in renewable systems, we introduce the OpenCEM Simulator and Dat
arXiv:2604.06395v1 Announce Type: new Abstract: Spiking reservoir computing provides an energy-efficient approach to temporal processing, but reliably tuning reservoirs to operate at the edge-of-chaos
arXiv:2604.08014v1 Announce Type: new Abstract: Spatio-Temporal Video Grounding requires jointly localizing target objects across both temporal and spatial dimensions based on natural language queries
arXiv:2604.05292v2 Announce Type: replace-cross Abstract: AI coding assistants are now used to generate production code in security-sensitive domains, yet the exploitability of their outputs remains u
arXiv:2506.12040v2 Announce Type: replace-cross Abstract: Binary quantization represents the most extreme form of compression, reducing weights to +/-1 for maximal memory and computational efficiency.
arXiv:2604.06752v1 Announce Type: new Abstract: We present EmBolic - a novel fully hyperbolic deep learning architecture for fine-grained emotion analysis from textual messages. The underlying idea is
arXiv:2604.06987v1 Announce Type: cross Abstract: Palmprint recognition is deployed in security-critical applications, including access control and palm-based payment, due to its contactless acquisiti
arXiv:2604.07286v1 Announce Type: cross Abstract: Autonomous vehicles deployed in remote environments typically rely on embedded processors, compact batteries, and lightweight sensors. These hardware
arXiv:2604.07009v1 Announce Type: new Abstract: Ensuring fairness in machine learning predictions is a critical challenge, especially when models are deployed in sensitive domains such as credit scori
arXiv:2604.06398v1 Announce Type: cross Abstract: Global ocean models exhibit biases in the mean state and variability, particularly at coarse resolution, where mesoscale eddies are unresolved. To add
arXiv:2604.07583v1 Announce Type: new Abstract: Real-world categorization is severely hampered by class imbalance because traditional ensembles favor majority classes, which lowers minority performanc
arXiv:2604.08287v1 Announce Type: new Abstract: Discovering camouflaged objects is a challenging task in computer vision due to the high similarity between camouflaged objects and their surroundings.
arXiv:2604.08294v1 Announce Type: cross Abstract: Action Quality Assessment (AQA) has broad applications in physical therapy, sports coaching, and competitive judging. Although Vision Language Models
arXiv:2510.18034v2 Announce Type: replace-cross Abstract: Autonomous driving systems remain critically vulnerable to the long-tail of rare, out-of-distribution semantic anomalies. While VLMs have emer
arXiv:2604.06718v2 Announce Type: cross Abstract: Repurchase behavior is a primary signal in large-scale retail recommendation, particularly in categories with frequent replenishment: many items in a
arXiv:2604.06808v1 Announce Type: cross Abstract: This paper presents CBM-Dual, the first silicon-proven digital chaotic dynamics processor (CDP) supporting both simulated annealing (SA) and reservoir
arXiv:2507.04678v3 Announce Type: replace Abstract: Spatiotemporal image generation is a highly meaningful task, which can generate future scenes conditioned on given observations. However, existing c
arXiv:2511.07797v2 Announce Type: replace Abstract: Vision-based tactile sensors (VBTSs) are a promising technology for robots, providing them with dense signals that can be translated into a multi-fa