Knowledge catalogue
arXiv:2411.14279v2 Announce Type: replace-cross Abstract: Large vision-language models (LVLMs) have achieved impressive results in various vision-language tasks. However, despite showing promising per
arXiv:2605.29798v1 Announce Type: new Abstract: Reliable identification of fracture origins in alumina matrix composite hip and knee implants is critical for quality assurance and patient safety, yet
arXiv:2605.29766v1 Announce Type: new Abstract: Imitation learning has become a cornerstone for solving complex robotic manipulation tasks. In particular, multimodality, which enables robots to captur
arXiv:2605.29498v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become one of the most widely used fine-tuning mechanisms for adapting large language models to new domains, tasks, and u
arXiv:2605.30046v1 Announce Type: cross Abstract: Anomaly detection aims to identify samples that deviate from the nominal data distribution and is central to many safety-critical applications. Howeve
arXiv:2601.03729v2 Announce Type: replace Abstract: Fine-grained recognition of marine organisms is important for ecological research, biodiversity monitoring, habitat conservation, and evidence-based
arXiv:2605.30190v1 Announce Type: new Abstract: Diffusion-based planning has achieved strong results in single-agent offline reinforcement learning, yet scaling to many-agent systems remains intractab
arXiv:2605.29212v1 Announce Type: new Abstract: Image quality in modern imaging systems emerges from the coupled effects of the sensor, optics, and computational reconstruction. Ultra-thin metalenses
arXiv:2605.29797v1 Announce Type: new Abstract: When annotators disagree on a label, the disagreement itself carries signal -- and the number of annotators needed to capture it depends on the evaluati
arXiv:2605.29987v1 Announce Type: cross Abstract: Although multi-scales representation learning enables elastic-dimension embeddings, nested subspaces often suffer from dimensional redundancy and spec
arXiv:2602.05370v3 Announce Type: replace Abstract: Iterative Direct Preference Optimization (DPO) has emerged as a widely used paradigm for aligning Large Language Models on reasoning tasks. Existing
arXiv:2605.29577v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a promising framework that unifies perception, reasoning, and control for robot manipulation by adap
arXiv:2510.27391v2 Announce Type: replace Abstract: Modality alignment is critical for vision-language models (VLMs) to effectively integrate information across modalities. However, existing methods e
arXiv:2507.00037v2 Announce Type: replace-cross Abstract: Model fusion seeks to combine independently trained neural networks into a single model without retraining, but is complicated by representati
arXiv:2510.22437v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) solve complex tasks by generating long Chain-of-Thought (CoT) sequences; however, the emergent dynamics governing reas
arXiv:2605.30187v1 Announce Type: new Abstract: The widespread adoption of AI chatbots in education will drastically change learning, making responsible deployment a critical concern. While large lang
arXiv:2605.30320v1 Announce Type: new Abstract: Existing inverse physics methods recover physical parameters from multi-view videos, where geometric constraints across views resolve scale and 3D struc
arXiv:2605.29138v1 Announce Type: cross Abstract: Latency-accuracy tradeoffs are fundamental in real-time applications of deep neural networks (DNNs) for cyber-physical systems. In autonomous driving,
Multiple executives tell me they’re looking to decrease their AI expenses just as three major AI IPOs are on the horizon. My latest: CEOs are bargain hunting for AI https://www.axios.com/2026/05/29/ce
arXiv:2605.30073v1 Announce Type: new Abstract: Joint audio-video generation aims to synthesize temporally synchronized and semantically coherent visual-acoustic content. However, existing open-source
arXiv:2605.30155v1 Announce Type: cross Abstract: The increasing integration of deep neural networks in critical systems has spawned a theoretical and practical interest in formally guaranteeing safet
arXiv:2605.30277v1 Announce Type: new Abstract: Real-time thermal-hydraulic simulation is essential for digital twin (DT) technology that supports the safe and efficient operation of small modular rea
Nobody knows for sure where employment is going and over what time frame. But one thing I can tell you for sure is that the big AI CEO’s have started lying about it. When they tell you know “we are ju
Note to all staff: Turns out that super tasty AI candy we've been putting out in large bowls isn't free and it isn't necessarily leading to better products for our customers. From now on, all employee
arXiv:2505.05968v3 Announce Type: replace Abstract: Offline cooperative multi-agent reinforcement learning (MARL) faces unique challenges due to distributional shifts, particularly stemming from the h
arXiv:2510.11499v2 Announce Type: replace-cross Abstract: Generative models have emerged as a powerful class of policies for offline reinforcement learning (RL) due to their ability to capture complex
arXiv:2605.29919v1 Announce Type: new Abstract: A central challenge in game theory and learning systems such as GANs is understanding which algorithms can efficiently compute equilibria across the het
arXiv:2505.24503v3 Announce Type: replace-cross Abstract: We study the problem of fairly allocating indivisible goods to agents in an online setting, where goods arrive sequentially and must be alloca
arXiv:2605.29885v1 Announce Type: new Abstract: Modern statistical learning theory and deep learning characterize generalization primarily in terms of continuous capacity control (e.g., norm-based reg
Gary Marcus expresses strong enthusiasm about Opus 4.8, suggesting it represents a significant breakthrough in AI capabilities. The post implies the model introduces substantial improvements or novel
arXiv:2605.29390v1 Announce Type: new Abstract: Text-to-image (T2I) models have become increasingly capable of generating high-quality images. Yet, enforcing the explicit absence of a specified object
arXiv:2605.29174v1 Announce Type: new Abstract: DeFi investment agents, systems that use AI for autonomous on-chain trading, have attained over USD 3 billion in combined token valuations since late 20
arXiv:2603.21621v2 Announce Type: replace Abstract: Classical on-policy algorithms such as PPO and mirror descent policy optimization provide stable proximal policy updates through tractable action li
arXiv:2605.29582v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown promise as educational tutors, yet effective tutoring requires more than solving problems: it must provide pro
arXiv:2510.08535v2 Announce Type: replace-cross Abstract: Diffusion models are central to generative modeling and have been adapted to graphs by diffusing adjacency matrix representations. The challen
arXiv:2506.06254v2 Announce Type: replace Abstract: Large Language Model (LLM) empowered agents have recently emerged as advanced paradigms that exhibit impressive capabilities in a wide range of doma
arXiv:2605.29407v1 Announce Type: new Abstract: This paper presents a phase-conditioned, force-aware framework for robust deformable object manipulation. Standard imitation learning policies such as A
arXiv:2605.29906v1 Announce Type: new Abstract: Text-to-motion (T2M) generation has broad applications in character animation, virtual avatars, and human-robot interaction. Existing methods typically
arXiv:2506.02075v2 Announce Type: replace-cross Abstract: The current state of evaluation in survival analysis is plagued by the persistent use of evaluation metrics in ways that are misaligned with t
arXiv:2605.29041v1 Announce Type: new Abstract: This study reports findings from a cross-sectional survey (n = 72) of higher education practitioners examining beliefs, behaviors, and institutional con
arXiv:2605.29119v1 Announce Type: new Abstract: Computer use agents (CUAs) have shown strong potential for automating complex digital workflows, yet their training remains constrained by costly live e
arXiv:2310.14161v2 Announce Type: replace Abstract: Machine learning has been successfully applied to improve the efficiency of Mixed-Integer Linear Programming (MILP) solvers. However, the learning-b
arXiv:2605.29251v1 Announce Type: new Abstract: As large language models transition from bounded generative engines to agents with expansive execution privileges, AI going out of control precipitates
arXiv:2605.29823v1 Announce Type: new Abstract: Deep networks often exhibit a preference for 'simple' solutions, and such a simplicity bias is widely believed to play a key role in generalization. Yet
arXiv:2605.28899v1 Announce Type: cross Abstract: Artificial Intelligence has achieved remarkable success across diverse application domains. However, its vulnerability to adversarial attacks poses si
quick, name a prominent company that achieved a major win via tokenmaxxing! I've yet to see, or hear of a company that is winning against its competition, because said company is spending more on AI t
arXiv:2605.29500v1 Announce Type: cross Abstract: Off-policy evaluation estimates how a target policy would perform using data collected by a different behavior policy, which is crucial when online te
arXiv:2605.29412v1 Announce Type: cross Abstract: This paper presents the real-time retargeting guidance policy developed for the Chandrayaan-3 lunar landing mission. The baseline guidance generates a
arXiv:2601.22139v2 Announce Type: replace-cross Abstract: Reasoning-oriented Large Language Models (LLMs) have achieved remarkable progress with Chain-of-Thought (CoT) prompting, yet they remain funda
arXiv:2605.29425v1 Announce Type: new Abstract: Reinforcement learning (RL) has shown promise in traffic signal control (TSC). However, its reliance on predefined states limits responsiveness to obser
arXiv:2605.29447v1 Announce Type: cross Abstract: While GUI agents have advanced rapidly, they often lack the robustness to recover from their own errors, hindering real-world deployment. To bridge th
arXiv:2602.20141v2 Announce Type: replace Abstract: Mean Field Games (MFGs) provide a principled framework for modelling interactions in large population systems. However, algorithmic progress has bee
arXiv:2605.26108v2 Announce Type: replace Abstract: Recent advances in few-step diffusion distillation have enabled efficient image generation, yet aligning these models with human preferences remains
arXiv:2605.29973v1 Announce Type: new Abstract: Robot behavior is often validated through simulation-based testing, yet the replicability of such campaigns depends critically on transparent documentat
arXiv:2605.28870v1 Announce Type: cross Abstract: We investigate the Platonic Representation Hypothesis (PRH) through a tripartite statistical framework of representations: signal, bias, and noise. {1
arXiv:2605.28850v1 Announce Type: new Abstract: We study behavioral alignment and representation dynamics of large language model (LLM) agents in financial decision environments. Using TradeArena, an
arXiv:2510.00936v2 Announce Type: replace Abstract: Cross-resolution person re-identification (CR-ReID) remains challenging in practical surveillance, where camera quality and capture distance lead to
arXiv:2605.28962v1 Announce Type: new Abstract: Diffusion bridge models offer a powerful framework for connecting two data distributions, such as in image restoration and translation. Many existing me
arXiv:2605.30338v1 Announce Type: new Abstract: Reconstructing physically stable 3D scenes from a single RGB image enables casual images to be converted into simulation-ready digital assets for applic
arXiv:2605.28897v1 Announce Type: new Abstract: LLM-generated reviews for scientific papers are gaining considerable traction and are even being officially piloted by major conferences. We have to ass