Knowledge catalogue
arXiv:2604.08588v1 Announce Type: cross Abstract: Effective automation hinges on deciding when to act and when to escalate. We model this as a decision under uncertainty: an LLM forms a prediction, es
ACTUAL BREAKING NEWS that sounds like an @TheOnion Headline: Florida man/Adjudicated rapist/convicted felon/one-time close personal friend with Jeffrey Epstein who has six corporate bankruptcies in hi
arXiv:2604.09462v1 Announce Type: new Abstract: Assistive teleoperation enhances efficiency via shared control, yet inter-operator variability, stemming from diverse habits and expertise, induces high
arXiv:2604.09035v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) with autoregressive world models suffers from compounding errors, whereas diffusion world models mitigate this
arXiv:2510.20512v2 Announce Type: replace Abstract: Recent progress in accelerating text-to-image diffusion models enables high-fidelity synthesis within a single denoising step. However, customizing
arXiv:2502.08691v2 Announce Type: replace-cross Abstract: Understanding human behavior and society is a central focus in social sciences, with the rise of generative social science marking a significa
A study has found that AI chatbots incorrectly diagnose patients in more than 80% of early medical cases, raising significant concerns about the reliability of AI tools in clinical settings. The resea
Alienated Europe Alienated the religious right Alienated Rogan, Carlson and many more Declared a war that even he can’t justify Messed up the Middle East Drove up the price of oil Drove up inflation U
arXiv:2602.13939v3 Announce Type: replace-cross Abstract: Business environments characterized by intermittent demand, high variability, and multi-step planning horizons require forecasting policies th
arXiv:2604.09288v1 Announce Type: new Abstract: Trusted multi-view classification typically relies on a view-wise evidential fusion process: each view independently produces class evidence and uncerta
arXiv:2604.08756v1 Announce Type: new Abstract: The situated view of cognition holds that intelligent behavior depends not only on internal memory, but on an agent's active use of environmental resour
As AI agents accelerate coding, what is the future of software engineering? Some trends are clear, such as the Product Management Bottleneck, referring to the idea that we are more constrained by deci
arXiv:2604.08355v2 Announce Type: replace Abstract: Reinforcement Learning (RL) agents often struggle to generalize knowledge to new tasks, even those structurally similar to ones they have mastered.
arXiv:2604.08999v1 Announce Type: cross Abstract: Table serialization remains a critical bottleneck for Large Language Models (LLMs) in complex table question answering, hindered by challenges such as
arXiv:2511.18960v3 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models have shown remarkable progress in embodied tasks recently, but most methods process visual observations in
arXiv:2405.16772v2 Announce Type: replace-cross Abstract: Social recommendation models weave social interactions into their design to provide uniquely personalized recommendation results for users. Ho
arXiv:2604.09260v1 Announce Type: new Abstract: Standard object detectors typically treat architectural elements independently, often resulting in facade parsings that lack the structural coherence re
arXiv:2604.08858v1 Announce Type: new Abstract: We present BIAS, a fast, biologically inspired model for dynamic visual saliency detection in continuous video streams. Building on the Itti--Koch frame
arXiv:2604.08357v2 Announce Type: replace Abstract: Conditional Diffusion Models are powerful surrogates for emulating complex spatiotemporal dynamics, yet they often fail to match the accuracy of det
arXiv:2604.07361v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have been widely used in diverse brain network analysis tasks based on preprocessed functional magnetic resonance imagi
arXiv:2604.08926v1 Announce Type: new Abstract: Post-training paradigms for Large Language Models (LLMs), primarily Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), face a fundamental dil
arXiv:2604.08757v1 Announce Type: cross Abstract: Humor is one of the most culturally embedded and socially significant dimensions of human communication, yet it remains largely unexplored as a dimens
arXiv:2509.25835v4 Announce Type: replace Abstract: Test-time scaling improves large language models (LLMs) on long-horizon reasoning tasks by allocating more compute at inference. LLM inference via t
arXiv:2505.18600v3 Announce Type: replace-cross Abstract: Modern single-image super-resolution (SISR) models deliver photo-realistic results at the scale factors on which they are trained, but collaps
arXiv:2507.04736v2 Announce Type: replace Abstract: Large Language Models have emerged as powerful tools for automating Register-Transfer Level (RTL) code generation, yet they face critical limitation
arXiv:2508.06656v2 Announce Type: replace Abstract: In-generation watermarking for latent diffusion models has recently shown high robustness in marking generated images for easier detection and attri
arXiv:2511.22963v2 Announce Type: replace-cross Abstract: Enabling humanoid robots to follow free-form language commands is critical for seamless human-robot interaction, collaborative task execution,
arXiv:2604.09308v1 Announce Type: new Abstract: Large language models are making autonomous drug discovery agents increasingly feasible, but reliable success in this setting is not determined by any s
arXiv:2604.09155v1 Announce Type: cross Abstract: Graphical user interface (GUI) agents powered by vision language models (VLMs) are rapidly moving from passive assistance to autonomous operation. How
arXiv:2604.08643v1 Announce Type: new Abstract: User interactions in online recommendation platforms create interdependencies among content creators: feedback on one creator's content influences the s
arXiv:2510.10181v3 Announce Type: replace-cross Abstract: Embodied agents face a fundamental limitation: once deployed in real-world environments, they cannot easily acquire new knowledge to improve t
arXiv:2601.22285v4 Announce Type: replace Abstract: Model merging combines knowledge from separately fine-tuned models, yet success factors remain poorly understood. While recent work treats mergeabil
arXiv:2604.08965v1 Announce Type: new Abstract: Semantic segmentation of satellite imagery plays a vital role in land cover mapping and environmental monitoring. However, annotating large-scale, high-
arXiv:2604.09455v1 Announce Type: new Abstract: While Large Language Models (LLMs) have demonstrated significant potential in Tool-Integrated Reasoning (TIR), existing training paradigms face signific
arXiv:2604.08706v1 Announce Type: new Abstract: While Experience Replay - the practice of storing rollouts and reusing them multiple times during training - is a foundational technique in general RL,
arXiv:2512.22437v2 Announce Type: replace Abstract: An image conveys meaning through both its visual content and emotional tone, jointly shaping human perception. We introduce Controllable Emotional I
arXiv:2604.08698v1 Announce Type: new Abstract: Tokens serve as the basic units of representation in DNA language models (DNALMs), yet their design remains underexplored. Unlike natural language, DNA
arXiv:2511.03913v2 Announce Type: replace-cross Abstract: Deep diffusion models have revolutionized image generation by producing high-quality outputs. However, achieving specific objectives with thes
arXiv:2602.07142v2 Announce Type: replace-cross Abstract: Collaboration is a cornerstone of 21st-century learning, yet teachers continue to face challenges in supporting productive peer interaction. E
arXiv:2604.08606v1 Announce Type: cross Abstract: One of the impediments to the efficiency of information markets is the inherent information asymmetry present in them, exacerbated by the 'buyer's ins
arXiv:2604.09064v1 Announce Type: new Abstract: In partial multi-label learning (PML), each instance is associated with a set of candidate labels containing both ground-truth and noisy labels. The pre
arXiv:2601.18150v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for large language models (LLMs) is increasingly bottlenecked by rollout (generation), where long output sequence
arXiv:2604.09063v1 Announce Type: cross Abstract: Human action recognition is pivotal in computer vision, with applications ranging from surveillance to human-robot interaction. Despite the effectiven
arXiv:2604.08617v1 Announce Type: cross Abstract: Exemplar replay has become an effective strategy for mitigating catastrophic forgetting in federated continual learning (FCL) by retaining representat
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
💯. “@garymarcus has won, others too” And the smart people already know it. AGI requires both symbols and neural networks. Period. The current regime in AI cannot possibly scale Mount AGI. Gary Marcus
arXiv:2604.06014v2 Announce Type: replace Abstract: We introduce Gated-SwinRMT, a family of hybrid vision transformers that combine the shifted-window attention of the Swin Transformer with the Manhat
This Reddit post on r/ChatGPT titled 'Gender bias' likely features a user-shared observation or experiment highlighting instances where ChatGPT exhibits gender-skewed responses, such as stereotyping o
General Purpose Technologies have downstream effects everywhere, good and bad. Those outcomes can be mitigated, or encouraged, with the right sorts of policy choices If the only options are being for
arXiv:2604.08664v1 Announce Type: new Abstract: Developing autonomous physical human-robot interaction (pHRI) systems is limited by the scarcity of large-scale training data to learn robust robot beha
arXiv:2604.08661v1 Announce Type: cross Abstract: Neural Quantum States based on autoregressive recurrent neural network (RNN) wave functions enable efficient sampling without Markov-chain autocorrela
arXiv:2604.08553v1 Announce Type: cross Abstract: Large Language Models (LLMs) have shown strong performance on text-attributed graphs (TAGs) due to their superior semantic understanding ability on te
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:2604.09231v1 Announce Type: new Abstract: Although recent advances have improved the quality of 3D texture generation, existing methods still struggle with incomplete texture coverage, cross-vie
arXiv:2510.26899v5 Announce Type: replace-cross Abstract: The launch of Grokipedia, an AI-generated encyclopedia developed by Elon Musk's xAI, was presented as a response to perceived ideological and
I am catching glimpses in my feed that there is a backlash against Mythos as 'marketing hype,' and it is a little confusing. I don't think anyone who has used the latest agentic coding tools, would th
arXiv:2603.02622v2 Announce Type: replace Abstract: While the Implicit Bias(or Implicit Regularization) of standard loss functions has been studied, the optimization geometry induced by discriminative
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:2604.09206v1 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: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