Knowledge catalogue
arXiv:2604.09240v1 Announce Type: new Abstract: High-Level Synthesis (HLS) compiles C/C++ into RTL, but exploring pragma-driven optimization choices remains expensive because each design point require
arXiv:2604.08574v1 Announce Type: cross Abstract: Large Genomic Foundation Models have recently achieved remarkable results and in-vivo translation capabilities. However these models quickly grow to o
arXiv:2604.09276v1 Announce Type: new Abstract: Distributed online convex optimization (D-OCO) is a powerful paradigm for modeling distributed scenarios with streaming data. However, the communication
arXiv:2602.10603v3 Announce Type: replace Abstract: Genomic foundation models have the potential to decode DNA syntax, yet face a fundamental tradeoff in their input representation. Standard fixed-voc
arXiv:2604.09189v1 Announce Type: cross Abstract: LLMs internalize safety policies through RLHF, yet these policies are never formally specified and remain difficult to inspect. Existing benchmarks ev
arXiv:2604.09425v1 Announce Type: new Abstract: Vision Language Models (VLMs) have achieved remarkable success by integrating visual encoders with large language models (LLMs). While VLMs process dens
arXiv:2604.09417v1 Announce Type: new Abstract: Many-objective optimisation, a subset of multi-objective optimisation, involves optimisation problems with more than three objectives. As the number of
arXiv:2604.09468v1 Announce Type: cross Abstract: In this study, we proposed a deep Swin-Vision Transformer-based transfer learning architecture for robust multi-cancer histopathological image classif
arXiv:2511.06756v3 Announce Type: replace Abstract: Over-smoothing remains a fundamental challenge in deep Graph Neural Networks (GNNs), where repeated message passing causes node representations to b
arXiv:2604.08791v1 Announce Type: cross Abstract: User-space Adaptive Bitrate (ABR) algorithms cannot see the transport layer signals that matter most, such as minimum RTT and instantaneous delivery r
arXiv:2604.09450v1 Announce Type: cross Abstract: Chest X-ray report generation (CXR-RG) has the potential to substantially alleviate radiologists' workload. However, conventional autoregressive visio
arXiv:2604.09164v1 Announce Type: new Abstract: Temporal human action detection aims to identify and localize action segments within untrimmed videos, serving as a pivotal task in video understanding.
arXiv:2604.09391v1 Announce Type: cross Abstract: Machine unlearning poses challenges in removing mislabeled, contaminated, or problematic data from a pretrained model. Current unlearning approaches a
arXiv:2604.09405v1 Announce Type: new Abstract: As text-to-image diffusion models grow increasingly prevalent, the ability to remove specific concepts-mostly explicit content and many copyrighted char
arXiv:2604.09168v1 Announce Type: new Abstract: We introduce Elastic Looped Transformers (ELT), a highly parameter-efficient class of visual generative models based on a recurrent transformer architec
arXiv:2604.09523v1 Announce Type: new Abstract: The transition of Multi-Agent Reinforcement Learning (MARL) policies from simulated cyber wargames to operational Security Operations Centers (SOCs) is
arXiv:2604.08708v1 Announce Type: cross Abstract: While Large Language Model-based Multi-Agent Systems (MAS) consistently outperform single-agent systems on complex tasks, their intricate interactions
arXiv:2604.08644v1 Announce Type: new Abstract: This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integr
arXiv:2510.09093v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now routinely used to autonomously execute complex tasks, from natural language processing to dynamic workflo
arXiv:2604.09174v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) aims to reduce hallucination by grounding answers in retrieved evidence, yet hallucinated answers remain common eve
arXiv:2603.23199v2 Announce Type: replace Abstract: Deep learning-based 3D medical image segmentation methods relies on large-scale labeled datasets, yet acquiring such data is difficult due to privac
Nous Research announced the release of Hermes Agent version 2026.4.13, with full release notes available on GitHub. The update can be applied using the command 'hermes update'. This appears to be a so
arXiv:2604.08581v1 Announce Type: new Abstract: This paper presents a fully autonomous Tiny Machine Learning (TinyML) Z-Score-based anomaly detection system deployed on a low-power microcontroller for
arXiv:2604.08576v1 Announce Type: cross Abstract: Sixth-generation (6G) wireless networks must support heterogeneous services: enhanced Mobile Broadband (eMBB) requiring 1 Tbps data rates, massive Mac
arXiv:2604.08894v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) offer superior energy efficiency over Artificial Neural Networks (ANNs). However, they encounter significant deficienci
arXiv:2510.24718v3 Announce Type: replace Abstract: Autoregressive video diffusion models are capable of long rollouts that are stable and consistent with history, but they are unable to guide the cur
arXiv:2604.08896v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) have accelerated progress in domain-oriented AI, yet their development in geoscience and rem
arXiv:2604.09304v1 Announce Type: new Abstract: For decades, Physically-Based Rendering (PBR) is the fundation of synthesizing photorealisitic images, and therefore sometimes roughly referred as Photo
arXiv:2604.08879v1 Announce Type: new Abstract: Moving beyond the traditional binary classification paradigm of Multimodal Sarcasm Detection, Multimodal Sarcasm Target Identification (MSTI) presents a
arXiv:2604.09222v1 Announce Type: cross Abstract: Audio large language models (ALLMs) enable rich speech-text interaction, but they also introduce jailbreak vulnerabilities in the audio modality. Exis
arXiv:2604.05072v2 Announce Type: replace Abstract: Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, ex
arXiv:2604.08884v1 Announce Type: cross Abstract: While multimodal large language models (MLLMs) have made significant strides in natural image understanding, their ability to perceive and reason over
arXiv:2604.09016v1 Announce Type: cross Abstract: This study addresses the challenge of creating datasets for cybercrime analysis while complying with the requirements of regulations such as the Gener
arXiv:2604.09135v1 Announce Type: cross Abstract: Unobserved confounding is a key challenge when estimating causal effects from a treatment on an outcome in scientific applications. In this work, we a
arXiv:2604.08762v1 Announce Type: cross Abstract: Understanding instructional videos requires recognizing fine-grained actions and modeling their temporal relations, which remains challenging for curr
arXiv:2604.09309v1 Announce Type: cross Abstract: The Half-Trek Criterion (HTC) is the primary graphical tool for determining generic identifiability of causal effect coefficients in linear structural
Harrison Chase, co-founder of LangChain, shared or engaged with a post on X (formerly Twitter) praising LangChain's developer relations team for producing high-quality technical and educational conten
arXiv:2604.09059v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have recently achieved notable progress in end-to-end autonomous driving by integrating perception, reasoning, and
arXiv:2604.08636v1 Announce Type: cross Abstract: Designing robot morphologies and kinematics has traditionally relied on human intuition, with little systematic foundation. Motion-design co-optimizat
arXiv:2506.22832v3 Announce Type: replace-cross Abstract: Training robust and generalizable reward models for human visual preferences is essential for aligning text-to-image and text-to-video generat
arXiv:2604.09360v1 Announce Type: cross Abstract: The rapid proliferation of Large Language Model (LLM) providers--each exposing proprietary API formats--has created a fragmented ecosystem where appli
arXiv:2604.08719v1 Announce Type: cross Abstract: Recent years have seen remarkable progress in autonomous driving, yet generalization to long-tail and open-world scenarios remains a major bottleneck
arXiv:2510.01767v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has established itself as an efficient representation for real-time, high-fidelity 3D scene reconstruction. However, sc
arXiv:2604.09206v1 Announce Type: new Abstract: Cooperative 3D perception via Vehicle-to-Everything communication is a promising paradigm for enhancing autonomous driving, offering extended sensing ho
arXiv:2502.02345v2 Announce Type: replace Abstract: Subspace inference for neural networks assumes that a subspace of their parameter space suffices to produce a reliable uncertainty quantification. I
Harrison Chase, co-founder and CEO of LangChain, expressed gratitude for his team in a post on X (formerly Twitter). The post likely highlights appreciation for colleagues and collaborators contributi
arXiv:2604.08952v1 Announce Type: new Abstract: Document Question Answering (DQA) involves generating answers from a document based on a user's query, representing a key task in document understanding
arXiv:2501.15461v4 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have shown great success in various graph-based learning tasks. However, it often faces the issue of over-smoothing as
arXiv:2604.08995v1 Announce Type: new Abstract: With the advancement of interactive video generation, diffusion models have increasingly demonstrated their potential as world models. However, existing
Maybe hot take - I’ve read a bunch of RL for image generation papers over last few months and honestly it’s been pretty disappointing. All of them are variations of GRPO and all of them are incrementa
arXiv:2604.09088v1 Announce Type: new Abstract: Memory-efficient transfer learning (METL) approaches have recently achieved promising performance in adapting pre-trained models to downstream tasks. Th
arXiv:2604.08799v1 Announce Type: cross Abstract: We propose MeshOn, a method that finds physically and semantically realistic compositions of two input meshes. Given an accessory, a base mesh with a
arXiv:2604.09338v1 Announce Type: new Abstract: Spatial reasoning is central to navigation and robotics, yet measuring model capabilities on these tasks remains difficult. Existing benchmarks evaluate
arXiv:2411.10636v2 Announce Type: replace-cross Abstract: In this study, we investigate extrinsic gender bias in Bangla pretrained language models, a largely underexplored area in low-resource languag
arXiv:2604.08712v1 Announce Type: new Abstract: The generation of planning domains from natural language descriptions remains an open problem even with the advent of large language models and reasonin
arXiv:2604.09253v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are powerful but remain vulnerable to multimodal jailbreak attacks. Existing attacks mainly rely on either explicit visu
arXiv:2502.13718v2 Announce Type: replace Abstract: Aspect-based sentiment analysis (ABSA) garnered growing research interest in multilingual contexts in the past. However, the majority of the studies
arXiv:2604.08782v1 Announce Type: new Abstract: Large language models (LLMs) suffer significant performance degradation when user instructions and context are distributed over multiple conversational
arXiv:2604.09326v1 Announce Type: cross Abstract: Ensuring safety and reliability in human-robot interaction (HRI) requires the timely detection of unexpected events that could lead to system failures
arXiv:2604.08582v1 Announce Type: cross Abstract: Multivariate Time Series Anomaly Detection (MTSAD) is critical for real-world monitoring scenarios such as industrial control and aerospace systems. M