Knowledge catalogue
arXiv:2604.13326v1 Announce Type: new Abstract: The robustness of machine learning models can be compromised by spurious correlations between non-causal features in the input data and target labels. A
arXiv:2604.13476v1 Announce Type: cross Abstract: Surround-view perception is increasingly important for robotic navigation and loco-manipulation, especially in human-in-the-loop settings such as tele
arXiv:2604.13806v1 Announce Type: new Abstract: Large Language Models (LLMs) are widely used across many domains, but their scale makes deployment challenging. Post-Training Quantization (PTQ) reduces
arXiv:2510.18165v2 Announce Type: replace-cross Abstract: Diffusion language models (DLMs) are emerging as a powerful and promising alternative to the dominant autoregressive paradigm, offering inhere
arXiv:2506.06114v4 Announce Type: replace Abstract: Unsupervised feature selection is critical for improving clustering performance in high-dimensional data, where irrelevant features can obscure mean
arXiv:2604.14026v1 Announce Type: new Abstract: Object extraction tasks often occur in disassembly problems, where bolts, screws, or pins have to be removed from tight, narrow spaces. In such problems
arXiv:2604.13941v1 Announce Type: new Abstract: Local feature matching plays a critical role in understanding the correspondence between cross-view images. However, traditional methods are constrained
arXiv:2604.13335v1 Announce Type: new Abstract: We introduce SEDTalker, an emotion-aware framework for speech-driven 3D facial animation that leverages frame-level speech emotion diarization to achiev
arXiv:2505.24869v3 Announce Type: replace Abstract: Recent advances in test-time optimization have led to remarkable reasoning capabilities in Large Language Models (LLMs), enabling them to solve high
arXiv:2604.13861v1 Announce Type: new Abstract: This paper develops a unified Markov Decision Process (MDP) framework for optimising two recurring in-match decisions in T20 cricket namely batting orde
arXiv:2604.13405v1 Announce Type: new Abstract: Singular configurations cause loss of task-space mobility, unbounded joint velocities, and solver divergence in inverse kinematics (IK) for serial manip
arXiv:2604.13295v1 Announce Type: new Abstract: t-SNE has gained popularity as a dimension reduction technique, especially for visualizing data. It is well-known that all dimension reduction technique
arXiv:2601.22795v2 Announce Type: replace Abstract: Transformer-based large language models (LLMs) are comprised of billions of parameters arranged in deep and wide computational graphs. Several studi
arXiv:2604.13333v1 Announce Type: new Abstract: We present SSD-GS, a physically-based relighting framework built upon 3D Gaussian Splatting (3DGS) that achieves high-quality reconstruction and photore
arXiv:2604.13297v1 Announce Type: cross Abstract: This paper investigates the problem of data-driven modeling of port-Hamiltonian systems while preserving their intrinsic Hamiltonian structure and sta
arXiv:2602.06264v2 Announce Type: replace Abstract: We consider the problem of minimizing different notions of swap regret in online optimization. These forms of regret are tightly connected to correl
Auto-generated synthesis of 1623 entries about arxiv-cs-ai
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Cyberscammers are bypassing banks’ security with illicit tools
arXiv:2505.12836v2 Announce Type: replace-cross Abstract: We consider the problem of sampling from a product-of-experts-type model that encompasses many standard prior and posterior distributions comm
As a movement, environmentalism has been pretty misanthropic. Understandably so—we humans have done some destructive things to the ecosystems around us. In the 21st century, though, mainstream conserv
arXiv:2510.03988v2 Announce Type: replace Abstract: Distilling long-form reasoning from teacher models into smaller students requires selecting which candidate solutions to train on. Recent work argue
There's a broadly held misconception in AI that methods that scale well are simple methods -- even, that simple methods usually scale. This is completely wrong. Pretty much none of the truly simple me
arXiv:2604.13186v1 Announce Type: new Abstract: Unsafe surgical care is a critical health concern, often linked to limitations in surgeon experience, skills, and situational awareness. Integrating pat
arXiv:2604.14069v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection is a longstanding computer vision problem concerned with predicting the interaction between humans and objects.
arXiv:2604.14074v1 Announce Type: new Abstract: Semantic Multi-Object Tracking (SMOT) extends multi-object tracking with semantic outputs such as video summaries, instance-level captions, and interact
arXiv:2601.07422v2 Announce Type: replace Abstract: Despite their impressive capabilities, large language models (LLMs) frequently generate hallucinations. Previous work shows that their internal stat
arXiv:2604.13565v1 Announce Type: new Abstract: Ultra-high-resolution (UHR) remote sensing imagery couples kilometer-scale context with query-critical evidence that may occupy only a few pixels. Such
arXiv:2604.13470v1 Announce Type: new Abstract: We prove that conditional diffusion models whose reverse kernels are finite Gaussian mixtures with ReLU-network logits can approximate suitably regular
arXiv:2604.13309v1 Announce Type: new Abstract: In this paper we present a novel visual servoing framework to control a robotic manipulator in the configuration space by using purely natural visual fe
arXiv:2604.13425v1 Announce Type: new Abstract: Video chroma-lux editing, which aims to modify illumination and color while preserving structural and temporal fidelity, remains a significant challenge
arXiv:2604.13687v1 Announce Type: cross Abstract: Glitches frequently contaminate data in gravitational-wave detectors, complicating the observation and analysis of astrophysical signals. This work in
Viktor Orbán’s electoral loss in Hungary is as much a defeat for Trump and JD Vance. 'Seldom have American leaders intervened so overtly in a foreign election, and seldom has their preferred candidate
arXiv:2506.01247v2 Announce Type: replace Abstract: Steering vision foundation models at test time, without updating foundation-model weights or using labeled target data, is a desirable yet challengi
arXiv:2604.02486v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have achieved impressive performance across a wide range of multimodal tasks. However, they often fail on tasks
arXiv:2604.13438v1 Announce Type: new Abstract: Privacy concerns in LLMs have led to the rapidly growing need to enforce a data's 'right to be forgotten'. Machine unlearning addresses precisely this t
arXiv:2604.13556v1 Announce Type: new Abstract: Cross-layer key-value (KV) compression has been found to be effective in efficient inference of large language models (LLMs). Although they reduce the m
arXiv:2511.05757v3 Announce Type: replace-cross Abstract: We introduce a differentiable framework for zero-shot adaptive control over parametric families of nonlinear dynamical systems. Our approach i
arXiv:2604.12027v1 Announce Type: new Abstract: Recently, the robotics community has regained interest in radar-based perception and state estimation. A 2D imaging radar provides dense 360deg informat
arXiv:2604.12434v1 Announce Type: cross Abstract: In-context learning enables transformers to adapt to new tasks from a few examples at inference time, while grokking highlights that this generalizati
arXiv:2603.10559v2 Announce Type: replace Abstract: This paper studies cross-market return predictability through a machine learning framework that preserves economic structure. Exploiting the non-ove
arXiv:2407.17182v4 Announce Type: replace Abstract: In this work, we consider the non-invasive medical imaging modality of Electrical Impedance Tomography (EIT), where the goal is to recover the condu
arXiv:2604.12211v1 Announce Type: new Abstract: Ollivier-Ricci curvature (ORC), defined via the Wasserstein distance that captures rich geometric information, has received growing attention in both th
arXiv:2603.18640v3 Announce Type: replace-cross Abstract: The No-U-Turn Sampler (NUTS) is the computational workhorse of modern Bayesian software libraries, yet its qualitative and quantitative conver
arXiv:2604.11927v1 Announce Type: new Abstract: Digital breast tomosynthesis (DBT) is now the standard of care for breast cancer screening in the USA. Accurate segmentation of fibroglandular tissue in
arXiv:2405.04108v2 Announce Type: replace-cross Abstract: Recent booming development of Generative Artificial Intelligence (GenAI) has facilitated model commercialization to reinforce the model perfor
arXiv:2604.12989v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive language models by using a lightweight drafter to propose multiple future tokens, which the target model
arXiv:2604.12792v1 Announce Type: new Abstract: In tendon driven continuum manipulators (TDCMs), reconfiguring the tendon routing enables tailored spatial deformation of the backbone. This work presen
arXiv:2501.16154v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown impressive multilingual capabilities through pretraining on diverse corpora. Although these models sho
arXiv:2604.12497v1 Announce Type: new Abstract: Large language models (LLMs) can generate survey responses at low cost, but their reliability varies substantially across questions and is unknown befor
arXiv:2603.18104v3 Announce Type: replace Abstract: Prevailing AI training infrastructure assumes reverse-mode automatic differentiation over IEEE-754 arithmetic. The memory overhead of training relat
arXiv:2604.12647v1 Announce Type: cross Abstract: Automated respiratory audio analysis promises scalable, non-invasive disease screening, yet progress is limited by scarce labeled data and costly expe
arXiv:2602.04204v2 Announce Type: replace Abstract: Human trajectory forecasting requires capturing the multimodal nature of pedestrian behavior. However, existing approaches suffer from prior misalig
arXiv:2604.06812v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated impressive capabilities in long-form generation, yet their application is hindered by the hallucinati
arXiv:2604.12811v1 Announce Type: cross Abstract: Dense Associative Memory (DAM) generalizes Hopfield networks through higher-order interactions and achieves storage capacity that scales as O(N^{n-1})
ARC-AGI-3 is a new benchmark iteration designed so that any intelligent human applying genuine effort should achieve greater than 90% accuracy, maintaining the benchmark's core principle that tasks mu
This r/MachineLearning discussion examines a growing concern in the AI and gaming community: that certain video game 'simulators' may be deliberately designed — or repurposed — to harvest player actio
arXiv:2604.12274v1 Announce Type: new Abstract: A class of planar bipedal robots with unique mechanical properties has been proposed, where all links are balanced around the hip joint, preventing natu
arXiv:2604.12480v1 Announce Type: cross Abstract: In Gaussian model-based multichannel audio source separation, the likelihood of observed mixtures of source signals is parametrized by source spectral
arXiv:2507.11081v3 Announce Type: replace-cross Abstract: Ground penetrating radar (GPR) has become a rapid and non-destructive solution for road subsurface distress (RSD) detection. However, recogniz
The question is no longer whether to deploy AI — it’s why so many deployments stall before delivering returns. The answer usually comes down to a lack of trusted data foundation. As research from Qlik