Knowledge catalogue
arXiv:2601.21257v2 Announce Type: replace Abstract: Advancing beyond single monolithic language models (LMs), recent research increasingly recognizes the importance of model collaboration, where multi
arXiv:2604.18226v1 Announce Type: new Abstract: Automated analysis of customer feedback on social media is hindered by three challenges: the high cost of annotated training data, the scarcity of evalu
arXiv:2604.16808v1 Announce Type: new Abstract: Current lip-sync deepfake detectors rely on pixel-level artifacts or audio-visual correspondence, failing to generalize across languages because these c
arXiv:2604.17199v1 Announce Type: new Abstract: Dielectric elastomer actuators (DEAs) have garnered extensive attention especially in soft robotic applications over the past few decades owing to the a
arXiv:2604.17713v1 Announce Type: new Abstract: Resting-state functional magnetic resonance imaging (fMRI) has emerged as a cornerstone for psychiatric diagnosis, yet most approaches rely on pairwise
arXiv:2604.18069v1 Announce Type: new Abstract: Humans often hold different perspectives on the same issues. In many NLP tasks, annotation disagreement can reflect valid subjective perspectives. Model
arXiv:2604.17174v1 Announce Type: new Abstract: Modeling human cognitive states is essential for advanced artificial intelligence. Existing Large Language Models (LLMs) mainly address isolated tasks s
arXiv:2604.17972v1 Announce Type: new Abstract: Emotional Support Conversation (ESC) aims to assist individuals experiencing distress by generating empathetic and supportive dialogue. While prior work
arXiv:2604.16419v1 Announce Type: cross Abstract: Fairness-aware recommender systems often mitigate bias by increasing exposure to under-represented or long-tail content, commonly through mechanisms t
arXiv:2604.16461v1 Announce Type: cross Abstract: Physics-guided sampling with diffusion priors has recently shown strong performance in solving complex systems of partial differential equations (PDEs
arXiv:2511.20853v3 Announce Type: replace Abstract: Reliable depth estimation under real optical conditions remains a core challenge for camera vision in systems such as autonomous robotics and augmen
arXiv:2604.18146v1 Announce Type: cross Abstract: Recently, large language models (LLMs) have advanced recommendation systems (RSs), and recent works have begun to explore how to integrate LLMs into i
arXiv:2604.17695v1 Announce Type: cross Abstract: KV cache memory is the dominant bottleneck for long-context LLM inference. Existing compression methods each act on a single axis of the four-dimensio
arXiv:2501.12281v2 Announce Type: replace Abstract: Given a partially observed road network, how can we predict the traffic state of interested unobserved locations? Traffic prediction is crucial for
arXiv:2604.17354v1 Announce Type: new Abstract: Vision-Language Models (VLMs) excel at photorealistic generation, yet often struggle to represent abstract meaning such as idiomatic interpretations of
arXiv:2603.21298v2 Announce Type: replace Abstract: Combating hate speech on social media is critical for securing cyberspace, yet relies heavily on the efficacy of automated detection systems. As con
arXiv:2603.19044v2 Announce Type: replace Abstract: Scientific ideation aims to propose novel solutions within a given scientific context. Existing LLM-based agentic approaches emulate human research
arXiv:2604.16503v1 Announce Type: new Abstract: Training strong video generation models usually requires massive datasets, large parameter counts, and substantial compute. In this work, we ask whether
arXiv:2604.17062v1 Announce Type: new Abstract: Zero-shot action recognition is challenging due to the semantic gap between seen and unseen classes. We present a novel framework that enhances CLIP wit
arXiv:2604.17435v1 Announce Type: new Abstract: Recent Speech-to-Speech Translation (S2ST) systems achieve strong semantic accuracy yet consistently strip away non-verbal vocalizations (NVs), such as
arXiv:2510.12831v3 Announce Type: replace Abstract: Multi-turn Text-to-SQL aims to translate a user's conversational utterances into executable SQL while preserving dialogue coherence and grounding to
arXiv:2604.17965v1 Announce Type: new Abstract: Generalizable Neural Radiance Fields (GeNeRFs) enable high-quality scene reconstruction from sparse views and can generalize to unseen scenes. However,
arXiv:2604.18583v1 Announce Type: new Abstract: Building photorealistic, animatable full-body digital humans remains a longstanding challenge in computer graphics and vision. Recent advances in animat
arXiv:2310.07464v2 Announce Type: replace-cross Abstract: Biomarker detection is an indispensable part of the diagnosis and treatment of low-grade glioma (LGG). However, current LGG biomarker detectio
arXiv:2604.17567v1 Announce Type: new Abstract: Multi-camera systems are widely employed in sports to capture the 3D motion of athletes and equipment, yet calibrating their extrinsic parameters remain
arXiv:2604.16468v1 Announce Type: new Abstract: Accurate phase equilibria are foundational to alloy design because they encode the underlying thermodynamics governing stability, transformations, and p
arXiv:2604.18477v1 Announce Type: new Abstract: Biological classification with interpretability remains a challenging task. For this, we introduce a novel encoding framework, Multi-Scale Reversible Ch
arXiv:2604.16962v1 Announce Type: new Abstract: Generating trajectories for synthetic aperture radar (SAR)-equipped aircraft poses significant challenges due to terrain constraints, and the need for s
arXiv:2604.18019v1 Announce Type: new Abstract: Sketch-based 3D shape retrieval (SBSR) aims to retrieve 3D shapes that are consistent with the category of the input hand-drawn sketch. The core challen
arXiv:2604.16577v1 Announce Type: new Abstract: Human activity recognition (HAR) refers to the process of identifying human actions and activities using data collected from sensors. Neural networks, s
arXiv:2604.18347v1 Announce Type: new Abstract: Vision Language Models (VLMs) achieved rapid progress in the recent years. However, despite their growth, VLMs development is heavily grounded on Englis
arXiv:2604.16311v1 Announce Type: new Abstract: Automated Fact-Checking (AFC) relies on claim extraction as a first step, yet existing methods largely overlook the multimodal nature of today's misinfo
arXiv:2604.17122v1 Announce Type: new Abstract: Breast cancer is a leading cause of cancer-related mortality worldwide, and timely accurate diagnosis is critical to improving survival outcomes. While
arXiv:2601.05707v2 Announce Type: replace Abstract: Automatic speech recognition (ASR) still covers only a small fraction of the world's languages, mainly due to supervised data scarcity. In-context l
arXiv:2510.09474v2 Announce Type: replace Abstract: Modern conversational agents like ChatGPT and Alexa+ rely on predefined policies specifying metadata, response styles, and tool-usage rules. As thes
arXiv:2401.10747v5 Announce Type: replace-cross Abstract: Multimodal sentiment analysis aims to identify the emotions expressed by individuals through visual, language, and acoustic cues. However, mos
arXiv:2604.18203v1 Announce Type: new Abstract: Multimodal LLMs can accurately perceive numerical content across modalities yet fail to perform exact multi-digit multiplication when the identical unde
arXiv:2604.18564v1 Announce Type: new Abstract: Video world models have achieved remarkable success in simulating environmental dynamics in response to actions by users or agents. They are modeled as
arXiv:2604.18090v1 Announce Type: new Abstract: Functional magnetic composites capable of large deformation, load bearing, and multifunctional motion are essential for next-generation adaptive soft ro
arXiv:2505.20715v2 Announce Type: replace-cross Abstract: Video temporal understanding is crucial for multimodal large language models (MLLMs) to reason over events in videos. Despite recent advances
arXiv:2603.20187v2 Announce Type: replace Abstract: Video-driven human reaction generation aims to synthesize 3D human motions that directly react to observed video sequences, which is crucial for bui
arXiv:2604.16967v1 Announce Type: new Abstract: Path planning is usually solved by addressing either the (high-level) route planning problem (waypoint sequencing to achieve the final goal) or the (low
arXiv:2411.05824v3 Announce Type: replace-cross Abstract: Medical Image Analysis (MedIA) has become indispensable in modern healthcare, enhancing clinical diagnostics and personalized treatment. Despi
arXiv:2604.17815v1 Announce Type: cross Abstract: When language models answer open-ended problems, they implicitly make hidden decisions that shape their outputs, leaving users with uncontextualized a
arXiv:2604.16581v1 Announce Type: new Abstract: Neural Combinatorial Optimization (NCO) has emerged as a powerful framework for solving combinatorial optimization problems by integrating deep learning
arXiv:2604.18235v1 Announce Type: new Abstract: Deep search agents can autonomously initiate multi-turn interactions with search engines, thereby exhibiting strong question-answering capabilities. Suc
arXiv:2604.17145v1 Announce Type: cross Abstract: This paper revisits momentum in the context of min-max optimization. Momentum is a celebrated mechanism for accelerating gradient dynamics in settings
arXiv:2604.16932v1 Announce Type: cross Abstract: Across many scientific fields, measurements often represent the number of times an event occurs. For example, a document can be represented by word oc
arXiv:2510.08726v2 Announce Type: replace-cross Abstract: Operator fusion has become a key optimization for deep learning, which combines multiple deep learning operators to improve data reuse and red
arXiv:2503.15845v2 Announce Type: replace Abstract: Network-wide Traffic State Estimation (TSE), which aims to infer a complete image of network traffic states with sparsely deployed sensors, plays a
arXiv:2604.17425v1 Announce Type: new Abstract: Meta-optics promises compact, high-performance imaging and color routing. However, designing high-performance structures is a high-dimensional optimizat
arXiv:2604.18002v1 Announce Type: new Abstract: Chain-of-thought reasoning has driven striking advances in language model capability, yet every reasoning step grows the KV cache, creating a bottleneck
arXiv:2604.17048v1 Announce Type: new Abstract: This paper investigates the control problem of dual-arm unmanned aerial manipulator systems (DAUAMs). Strong coupling between the dual-arm and the multi
arXiv:2401.15604v4 Announce Type: replace Abstract: Diffusion models have become a leading paradigm in generative AI, with score estimation via denoising score matching as a central component. While r
arXiv:2301.13331v3 Announce Type: replace-cross Abstract: Numerical approximations of partial differential equations (PDEs) are routinely employed to formulate the solution of physics, engineering, an
arXiv:2604.18012v1 Announce Type: new Abstract: We prove error bounds for operator surrogates of solution operators for partial differential and boundary integral equations on families of domains whic
arXiv:2604.17340v1 Announce Type: new Abstract: Clinical guidelines, typically developed by independent specialty societies, inherently exhibit substantial fragmentation, redundancy, and logical contr
arXiv:2601.19079v2 Announce Type: replace Abstract: Conventional robotic Braille readers typically rely on discrete, character-by-character scanning, limiting reading speed and disrupting natural flow
arXiv:2604.16722v1 Announce Type: new Abstract: Predicting full-field physics through the real-time virtual sensing of engineering systems can enhance limited physical sensors but often requires spars
arXiv:2509.26010v2 Announce Type: replace Abstract: Second-order PDE models have been widely used for suppressing multiplicative noise, but they often introduce blocky artifacts in the early stages of