Knowledge catalogue
arXiv:2505.21072v4 Announce Type: replace Abstract: Large Language Models (LLMs) enhanced with retrieval, an approach known as Retrieval-Augmented Generation (RAG), have achieved strong performance in
arXiv:2604.16298v1 Announce Type: new Abstract: UAV vision-language navigation (VLN) requires an agent to navigate complex 3D environments from an egocentric perspective while following ambiguous mult
arXiv:2604.15395v1 Announce Type: new Abstract: Over the recent years, the field of robotics has been undergoing a transformative paradigm shift from fixed, single-task, domain-specific solutions towa
arXiv:2604.15948v1 Announce Type: new Abstract: Text-guided image editing, a pivotal task in modern multimedia content creation, has seen remarkable progress with training-free methods that eliminate
arXiv:2604.15800v1 Announce Type: cross Abstract: This study presents WriteFlow, an AI voice-based writing assistant designed to support reflective academic writing through goal-oriented interaction.
arXiv:2502.19312v2 Announce Type: replace-cross Abstract: Effective personalization of LLMs is critical for a broad range of user-interfacing applications such as virtual assistants and content curati
arXiv:2604.15482v1 Announce Type: cross Abstract: Large Language Models (LLMs) unlearning is crucial for removing hazardous or privacy-leaking information from the model. Practical LLM unlearning dema
arXiv:2604.15648v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) consistently require new arenas to guide their expanding boundaries, yet their capabilities with hypergraphs remain
arXiv:2604.15642v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown promising progress for generating Register Transfer Level (RTL) hardware designs, largely because they can rap
arXiv:2604.15607v1 Announce Type: cross Abstract: AI design characteristics and human personality traits each impact the quality and outcomes of human-AI interactions. However, their relative and join
arXiv:2512.07173v4 Announce Type: replace Abstract: We present CadLLM, a training-free method to accelerate the inference throughput of diffusion-based LLMs (dLLMs). We first investigate the dynamic n
arXiv:2604.16264v1 Announce Type: new Abstract: Vision Language models (VLMs) have demonstrated strong performance across a wide range of benchmarks, yet they often suffer from modality dominance, whe
arXiv:2604.15951v1 Announce Type: new Abstract: Generative AI, particularly Large Language Models, increasingly integrates graph-based representations to enhance reasoning, retrieval, and structured d
arXiv:2505.13792v2 Announce Type: replace-cross Abstract: Recent advances in reasoning-focused Large Language Models (LLMs) have introduced Chain-of-Thought (CoT) traces - intermediate reasoning steps
arXiv:2604.15449v1 Announce Type: new Abstract: Kalman filter-based algorithms are fundamental for mobile robots, as they provide a computationally efficient solution to the challenging problem of sta
arXiv:2604.16247v1 Announce Type: cross Abstract: We propose HILBERT (HIerarchical Long-sequence Balanced Embedding with Reciprocal contrastive Training), a cross-attentive multimodal framework for le
Kimi K2.6 is an open-source model featuring advanced coding, long-horizon execution, and agent swarm capabilities that is now available via Ollama Cloud . The model excels in coding and agentic tools
arXiv:2406.15809v5 Announce Type: replace Abstract: Citizen reporting platforms help the public and authorities stay informed about sexual harassment incidents. However, the high volume of data shared
arXiv:2604.15744v1 Announce Type: new Abstract: This thesis investigates geographic dialect alignment in place-informed social media communities, focussing on New Zealand-related Reddit communities. B
arXiv:2604.15726v1 Announce Type: new Abstract: This position paper argues that large language model (LLM) reasoning should be studied as latent-state trajectory formation rather than as faithful surf
arXiv:2604.16058v1 Announce Type: cross Abstract: The rapid proliferation of Large Language Models (LLMs) in software development has made distinguishing AI-generated code from human-written code a cr
A benchmarking post testing 63 different samplers combined with the linear_quadratic noise scheduler for LTX-2.3 (Lightricks' audio-video generation model) . The linear_quadratic scheduler was origina
arXiv:2604.14334v2 Announce Type: replace-cross Abstract: Gradient saliency from deep sequence models surfaces candidate biomarkers efficiently, but the resulting gene lists can be contaminated by tis
arXiv:2601.03633v2 Announce Type: replace-cross Abstract: Accurate and high-resolution precipitation nowcasting from radar echo sequences is crucial for disaster mitigation and economic planning, yet
arXiv:2604.14518v2 Announce Type: replace Abstract: We present Mind DeepResearch (MindDR), an efficient multi-agent deep research framework that achieves leading performance with only ~30B-parameter m
arXiv:2510.09065v2 Announce Type: replace-cross Abstract: We introduce MMAudioSep, a generative model for video/text-queried sound separation that is founded on a pretrained video-to-audio model. By l
arXiv:2604.15979v1 Announce Type: new Abstract: Gait recognition has emerged as a powerful biometric technique for identifying individuals at a distance without requiring user cooperation. Most existi
arXiv:2604.15325v1 Announce Type: cross Abstract: This paper presents the design of NEFFY 2.0, a social robot designed as a haptic slow-paced breathing companion for stress reduction, and reports find
arXiv:2604.15694v1 Announce Type: new Abstract: Discrete diffusion models based on continuous-time Markov chains (CTMCs) have shown strong performance on language and discrete data generation, yet exi
arXiv:2604.16170v1 Announce Type: new Abstract: We introduce neuralCAD-Edit, the first benchmark for editing 3D CAD models collected from expert CAD engineers. Instead of text conditioning as in prior
arXiv:2604.15718v1 Announce Type: cross Abstract: Visual speaker recognition based on lip motion offers a silent, hands-free, and behavior-driven biometric solution that remains effective even when ac
arXiv:2604.16021v1 Announce Type: cross Abstract: Code localization is a cornerstone of autonomous software engineering. Recent advancements have achieved impressive performance on real-world issue be
Nice paper combining the strength of Skills and RAG. Most RAG systems retrieve on every query, whether the model needs help or not. This is wasteful when the model already knows the answer, and often
arXiv:2604.16275v1 Announce Type: new Abstract: This paper explores the response of Large Language Models (LLMs) to user prompts with different degrees of politeness and impoliteness. The Politeness T
arXiv:2604.03444v3 Announce Type: replace-cross Abstract: Recent work has demonstrated the potential of non-transformer language models, especially linear recurrent neural networks (RNNs) and hybrid m
arXiv:2604.16235v1 Announce Type: new Abstract: This paper presents a systematic benchmark of state-of-the-art multilingual large language models (LLMs) adapted via token pruning - a compression techn
arXiv:2604.15549v1 Announce Type: new Abstract: We consider the problem of minimizing the convergence time for decentralized federated learning (DFL) in wireless networks under broadcast communication
arXiv:2604.15483v1 Announce Type: new Abstract: We present a new robotic foundation model, called {pi}_{0.7}, that can enable strong out-of-the-box performance in a wide range of scenarios. {pi}_{0.7}
arXiv:2504.03621v2 Announce Type: replace Abstract: Classical OCR pipelines decompose document reading into detection, segmentation, and recognition stages, which makes them sensitive to localization
arXiv:2510.22149v3 Announce Type: replace-cross Abstract: Federated learning (FL) has emerged as a promising paradigm for decentralized model training, enabling multiple clients to collaboratively lea
arXiv:2604.15385v1 Announce Type: cross Abstract: Software documentation is essential for program comprehension, developer onboarding, code review, and long-term maintenance. Yet producing quality doc
arXiv:2604.15494v1 Announce Type: cross Abstract: Deep networks that rely on prototypes-interpretable representations that can be related to the model input-have gained significant attention for balan
arXiv:2604.15780v1 Announce Type: cross Abstract: Machine learning models are increasingly deployed in real-world applications, but even aligned models such as Mistral and LLaVA still exhibit unsafe b
arXiv:2604.15464v1 Announce Type: cross Abstract: Large Language Model (LLM) deployment is increasingly shifting to cost-efficient accelerators like Google's Tensor Processing Units (TPUs), prioritizi
arXiv:2604.15994v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) excel at recognizing individual visual elements and reasoning over simple linear diagrams. However, when faced
arXiv:2511.03056v2 Announce Type: replace-cross Abstract: Conversational AI is constrained in many real-world settings where only one side of a dialogue can be recorded, such as telemedicine, call cen
This article analyzes the performance differences between open-source and closed-source AI models in the current landscape, examining factors that influence their relative capabilities and market posi
arXiv:2604.16106v1 Announce Type: cross Abstract: The Project of AI is a world-building endeavor, wherein those who fund and develop AI systems both operate through and seek to sustain networks of pow
arXiv:2604.15621v1 Announce Type: cross Abstract: Adaptive Retrieval-Augmented Generation aims to mitigate the interference of extraneous noise by dynamically determining the necessity of retrieving s
arXiv:2604.16090v1 Announce Type: cross Abstract: Probabilistic Synchronous Parallel (PSP) is a technique in distributed learning systems to reduce synchronization bottlenecks by sampling a subset of
arXiv:2604.16200v1 Announce Type: new Abstract: This paper presents a novel saturation aware space variant blind image deblurring framework designed to address challenges posed by saturated pixels in
arXiv:2603.03188v2 Announce Type: replace-cross Abstract: We introduce a novel framework for uncertainty quantification in clustering that combines martingale posterior distributions with density-base
arXiv:2602.11327v2 Announce Type: replace-cross Abstract: The rapid development of the AI agent communication protocols, including the Model Context Protocol (MCP), Agent2Agent (A2A), Agora, and Agent
arXiv:2603.20633v3 Announce Type: replace Abstract: We present Seed1.8, a foundation model aimed at generalized real-world agency: going beyond single-turn prediction to multi-turn interaction, tool u
arXiv:2509.05489v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards has significantly advanced reasoning in large language models (LLMs), but such signals remain coarse,
arXiv:2604.15783v1 Announce Type: new Abstract: Urban bike-sharing systems require strategic station expansion to meet growing demand. Traditional allocation approaches rely on explicit demand modelli
arXiv:2604.15628v1 Announce Type: cross Abstract: Cross-modal retrieval between food images and recipe texts is an important task with applications in nutritional management, dietary logging, and cook
arXiv:2604.16197v1 Announce Type: new Abstract: Data attribution and valuation are critical for understanding data-model synergy for Large Language Models (LLMs), yet existing gradient-based methods s
arXiv:2604.15347v1 Announce Type: cross Abstract: Autism Spectrum Disorder (ASD) affects more than 75 million people worldwide. However, scalable support for practicing everyday conversation is scarce
arXiv:2511.20834v2 Announce Type: replace-cross Abstract: Sparse Convolution (SpC) powers 3D point cloud networks widely used in autonomous driving and augmented/virtual reality. SpC builds a kernel m