Knowledge catalogue
arXiv:2605.07003v1 Announce Type: new Abstract: The interaction of robots with bendable objects in midair presents significant challenges in control, often resulting in performance degradation and pot
arXiv:2511.09598v5 Announce Type: replace Abstract: Many real-world applications require solving families of expensive multi-objective optimization problems~(EMOPs) under varying operational condition
arXiv:2605.07317v1 Announce Type: cross Abstract: Vision Transformers (ViTs) achieve strong performance across vision tasks, yet their deployment with low-precision early exiting remains fragile. Exis
arXiv:2605.06759v1 Announce Type: new Abstract: The decline of natural pollinators has created a major challenge for crop production in controlled indoor agriculture, particularly in vertical farming
arXiv:2602.19612v3 Announce Type: replace Abstract: Machine Unlearning (MU) enables Large Language Models (LLMs) to remove unsafe or outdated information. However, existing work assumes that all facts
arXiv:2605.06834v1 Announce Type: new Abstract: Continual learning research attempts to conserve two fundamental capabilities: new knowledge acquisition and the preservation of previously acquired kno
arXiv:2605.07478v1 Announce Type: new Abstract: Speech-driven facial animation requires accurate correspondence between acoustic signals and facial motion, especially for articulation-related mouth mo
arXiv:2605.07883v1 Announce Type: new Abstract: Large Language Models (LLMs) rely on safety alignment to obey safe requests while refusing harmful ones. However, traditional refusal mechanisms often l
arXiv:2605.07333v1 Announce Type: new Abstract: In-context reinforcement learning (ICRL) studies agents that, after pretraining, adapt to new tasks by conditioning on additional context without parame
arXiv:2605.04615v2 Announce Type: replace-cross Abstract: Code search has usually been evaluated as first-stage retrieval, even though production systems rely on broader pipelines with reranking and d
arXiv:2605.07084v1 Announce Type: new Abstract: Automatic speech recognition (ASR) evaluation compares system output to ground truth transcripts, with Word Error Rate (WER) quantifying the distance be
arXiv:2605.06890v1 Announce Type: new Abstract: AI agents are promising for high-stakes enterprise workflows, but dependable deployment remains limited because tool-use failures are difficult to diagn
arXiv:2602.17407v2 Announce Type: replace-cross Abstract: Phased-array Bluetooth systems have emerged as a low-cost alternative for performing aided inertial navigation in GNSS-denied use cases such a
arXiv:2605.07605v1 Announce Type: new Abstract: Autonomous robotic assembly of interlocking bricks demands seamless integration of long-horizon task reasoning, spatial grounding, and fine-grained mani
arXiv:2509.08318v2 Announce Type: replace Abstract: Early-exit cascades over a frozen convolutional backbone enable adaptive inference but suffer from three sources of train-inference mismatch: branch
arXiv:2605.06702v1 Announce Type: new Abstract: Large language models (LLMs) have become a central foundation of modern artificial intelligence, yet their lifecycle remains constrained by a rigid sepa
arXiv:2602.01621v3 Announce Type: replace-cross Abstract: Homomorphic encryption (HE) is a prominent framework for privacy-preserving machine learning, enabling inference directly on encrypted data. H
Luke James / Tom's Hardware: Chinese state media: CAS Cold Atom Technology has built the 200-qubit Hanyuan-2, the world's first dual-core quantum computer, with a core for error correction — Metrics a
arXiv:2605.07162v1 Announce Type: new Abstract: Personalized LLMs can significantly enhance user experiences by tailoring responses to preferences such as helpfulness, conciseness, and humor. However,
arXiv:2605.07905v1 Announce Type: cross Abstract: Despite the rapid development of AI reviewers, evaluating such systems remains challenging: metrics favor overlap with human reviews over correctness.
arXiv:2605.07764v1 Announce Type: new Abstract: Natural-language interfaces can make swarm robotics more accessible to non-expert operators, but they must translate ambiguous user intent into executab
arXiv:2605.06788v1 Announce Type: new Abstract: When multi-agent systems (MAS) fail, identifying where the decisive error occurred is the first step for automated recovery to an earlier state. Error a
arXiv:2605.07123v1 Announce Type: new Abstract: In-context reinforcement learning (ICRL) refers to the ability of RL agents to adapt to new tasks at inference time without parameter updates by conditi
arXiv:2508.01994v2 Announce Type: replace Abstract: As the application of deep learning in dermatology continues to grow, the recognition of melanoma has garnered significant attention, demonstrating
arXiv:2605.07503v1 Announce Type: new Abstract: Efficiently aligning large-scale video diffusion models with human intent requires a scalable and trajectory-aware pathway that bridges the inherent dis
arXiv:2605.07151v1 Announce Type: cross Abstract: Urban spatial evolution is manifested not only through horizontal expansion but also through vertical structural changes. Consequently, jointly captur
arXiv:2605.07011v1 Announce Type: new Abstract: Motivational-interviewing-based health coaching is an effective approach for improving mental health and promoting healthy behavior change. However, the
arXiv:2508.06816v3 Announce Type: replace Abstract: Lesion segmentation, in contrast to natural scene segmentation, requires handling subtle variations in texture and color, frequent imaging artifacts
arXiv:2603.14787v2 Announce Type: replace Abstract: Pneumatically-actuated anthropomorphic robots with high degrees of freedom (DOF) offer significant potential for physical human-robot interaction. H
arXiv:2605.07299v1 Announce Type: cross Abstract: Existing Multimodal Large Language Models (MLLMs) remain primarily reactive, failing to continuously perceive environments or proactively assist users
arXiv:2605.06875v1 Announce Type: cross Abstract: Advanced driver-assistance systems (ADAS) require neural compute engines that deliver low-latency inference under strict power and area constraints. P
arXiv:2605.06280v2 Announce Type: replace Abstract: Recent advancements in image animation have utilized diffusion models to breathe life into static images. However, existing controllable frameworks
arXiv:2605.07988v1 Announce Type: new Abstract: The spine plays a crucial role in the dynamic locomotion of quadrupedal animals, improving the stability, speed, and efficiency of their gait, especiall
arXiv:2605.07947v1 Announce Type: cross Abstract: The escalating complexity of modern machine learning necessitates solving challenging non-convex optimization problems, particularly in high-dimension
arXiv:2510.02371v2 Announce Type: replace-cross Abstract: Smart grids are exposed to passive eavesdropping, where attackers listen silently to communication links. Although no data is actively altered
arXiv:2605.07145v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown strong potential for scientific image understanding, but general-purpose models often lack the domain-specifi
arXiv:2605.07914v1 Announce Type: cross Abstract: Sharpness-aware and gradient-alignment methods have been shown to improve generalization, however each family of methods targets a single geometric pr
arXiv:2602.09782v2 Announce Type: replace-cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a critical method for enhancing the reasoning capabilities of Large Langu
arXiv:2605.07364v1 Announce Type: new Abstract: Flight delays impose cascading operational and financial burdens across the aviation network, costing the U.S. economy billions of dollars annually by d
arXiv:2605.07474v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models hold great promise for general-purpose robotic intelligence, yet scaling up such models is severely bottlenecked b
arXiv:2605.07062v1 Announce Type: cross Abstract: AI agents are assuming active roles in Continuous Integration and Continuous Deployment (CI/CD) workflows, yet the research community lacks a shared v
arXiv:2605.07861v1 Announce Type: new Abstract: Makeup transfer aims to apply the makeup style of a reference portrait to a source portrait while preserving identity and background. Early methods form
arXiv:2605.07961v1 Announce Type: new Abstract: Federated fine-tuning (FFT) has emerged as a privacy-preserving paradigm for collaboratively adapting large language models (LLMs). Built upon federated
arXiv:2603.19966v2 Announce Type: replace Abstract: Wind disturbances remain a key barrier to reliable autonomous navigation for lightweight quadrotors, where the rapidly varying airflow can destabili
arXiv:2509.08089v2 Announce Type: replace Abstract: Federated Learning (FL) enables distributed model training but is vulnerable to backdoor attacks, where malicious clients embed attacker-controlled
arXiv:2605.07397v1 Announce Type: new Abstract: After a somewhat rocky start, geometry and topology have established a foothold in machine learning. Message passing, either on graphs or higher-order c
arXiv:2605.07472v1 Announce Type: cross Abstract: Insider threat detection assumes that an adaptive insider leaves behavioral residue distinguishing them from legitimate users. We test this assumption
arXiv:2605.06882v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved great improvements in recent years. Nevertheless, it still remains unclear how good LLMs are for reasoning ta
arXiv:2605.07545v1 Announce Type: cross Abstract: Human image animation has witnessed significant advancements, yet generating high-fidelity hand motions remains a persistent challenge due to their hi
arXiv:2605.07218v1 Announce Type: new Abstract: For continuous state-action space scenarios, classical reinforcement learning (RL) theory predominantly focuses on low-rank Markov decision processes (M
arXiv:2605.07930v1 Announce Type: cross Abstract: Differential privacy (DP) is widely employed in machine learning to protect confidential or sensitive training data from being revealed. As data owner
arXiv:2605.07733v1 Announce Type: cross Abstract: Accurate truck-to-shipment matching using GPS data is foundational for full truckload supply chain visibility, enabling real-time tracking and accurat
arXiv:2603.03096v2 Announce Type: replace-cross Abstract: How do speech models trained through self-supervised learning structure their representations? Previous studies have looked at how information
arXiv:2605.07622v1 Announce Type: new Abstract: Gender bias in large language models has primarily been investigated for English, while languages with grammatical or morphological gender remain compar
arXiv:2511.09907v5 Announce Type: replace Abstract: Data synthesis for training large reasoning models offers a scalable alternative to limited, human-curated datasets, enabling the creation of high-q
arXiv:2605.05615v2 Announce Type: replace Abstract: Large language models (LLMs) impose rapidly growing energy demands, creating an emerging energy and carbon crisis driven by large-scale inference. S
arXiv:2605.06933v1 Announce Type: new Abstract: Our computing ecosystem is being transformed by two emerging paradigms: the increased deployment of agentic AI systems and advancements in quantum compu
arXiv:2605.05949v2 Announce Type: replace Abstract: Algorithmic problem solving serves as a rigorous testbed for evaluating structured reasoning in AI coding systems, as it directly reflects a model's
arXiv:2605.07178v1 Announce Type: new Abstract: Remote sensing change detection is pivotal for urban monitoring, disaster assessment, and environmental resource management. Yet, unimodal deep learning
arXiv:2605.07850v1 Announce Type: cross Abstract: With the rise in scale for deep learning models to billions of parameters, the computational cost of fine-tuning remains a significant barrier to depl