Knowledge catalogue
arXiv:2601.08955v3 Announce Type: replace-cross Abstract: Recent advances in world models have shown promise for modeling future dynamics of environmental states, enabling agents to reason and act wit
arXiv:2609.04014v1 Announce Type: new Abstract: For trained operators, gauge reading requires little specialized knowledge, low cognitive effort, and high repeatability. Yet Multimodal Large Language
It's weird thinking back to 6 weeks ago, when I and others thanked OpenAI for disclosing the HF incident, now that we know they were covering up a 2nd incident. Are there more incidents that they know
arXiv:2609.03148v1 Announce Type: new Abstract: Most prior works focused on conflicts between an LLM's internal parametric knowledge and externally provided context. In contrast, we investigate how LL
arXiv:2609.03528v1 Announce Type: cross Abstract: Diffusion reinforcement learning (RL) has recently achieved significant success in post-training image and video generative models. However, most diff
arXiv:2609.03330v1 Announce Type: new Abstract: Moral language plays a central role in shaping online endorsement and the diffusion of information, yet existing moral foundation detection systems ofte
arXiv:2503.03313v4 Announce Type: replace-cross Abstract: Text-Attributed Graphs (TAGs), where each node is associated with text descriptions, are ubiquitous in real-world scenarios. They typically ex
arXiv:2609.03209v1 Announce Type: new Abstract: We study a governed approach to enterprise analytics: a language model interprets the question, while deterministic policy selects and runs a pre-approv
arXiv:2609.03415v1 Announce Type: new Abstract: Automatic generation of hand gestures is essential for the transmission of Indian classical dance and critical for its preservation. Indian classical da
arXiv:2609.03984v1 Announce Type: new Abstract: Quadruped robots have demonstrated impressive agility in parkour locomotion across complex terrains. However, most systems still rely on human intervent
arXiv:2609.03842v1 Announce Type: new Abstract: Offline reinforcement learning (RL) must reconcile two competing requirements: policy updates should stay near dataset-supported actions to keep value e
arXiv:2609.03527v1 Announce Type: new Abstract: Neonatal respiratory diseases are a major cause of neonatal morbidity and mortality, posing substantial challenges in clinical practice. Despite recent
arXiv:2609.03520v1 Announce Type: cross Abstract: In conditional coding-based neural video compression, the quality of temporal context directly affects compression per- formance. Existing methods mos
arXiv:2609.03160v1 Announce Type: new Abstract: Nastase et al. (2026) argue that large language models (LLMs) may illuminate language processing because both rely on distributed, context-sensitive rep
arXiv:2602.01207v2 Announce Type: replace Abstract: Offline preference optimization aligns reasoning models from fixed chosen--rejected pairs, yet standard methods apply gradient updates from every pa
arXiv:2601.10029v3 Announce Type: replace Abstract: Academic paper search is a fundamental task in scientific research, yet most existing approaches organize retrieval around predefined workflows or s
arXiv:2609.03180v1 Announce Type: new Abstract: When a statistical agency or regulator releases synthetic data in place of sensitive records, it chooses the generator that produces the table, and can
arXiv:2603.28763v2 Announce Type: replace Abstract: Acquiring labeled datasets for 3D human mesh estimation is challenging due to depth ambiguities and the inherent difficulty of annotating 3D geometr
arXiv:2609.03503v1 Announce Type: new Abstract: With the rapid development of the Internet of Things, computation intensive directed acyclic graph (DAG) tasks have become increasingly common in cloud-
arXiv:2609.03420v1 Announce Type: cross Abstract: Federated learning enables privacy-conscious collaboration for network intrusion detection without centralizing sensitive traffic data, yet its deploy
arXiv:2601.05250v2 Announce Type: replace Abstract: Quantum implicit neural representations have recently emerged as compact function approximators for continuous visual signals. In parallel, Neural R
arXiv:2609.03276v1 Announce Type: new Abstract: Evaluating robot manipulation policies is becoming increasingly important as generalist models, particularly vision-language-action (VLA) models, are de
arXiv:2609.03619v1 Announce Type: cross Abstract: Multi-agent debate (MAD) improves the reasoning capabilities of large language models by having multiple agents iteratively refine their responses thr
arXiv:2609.04172v1 Announce Type: new Abstract: On-policy distillation (OPD) combines student-generated rollouts with dense token-level supervision from a teacher. Existing work has mainly studied its
arXiv:2609.03906v1 Announce Type: new Abstract: Vision-Language Navigation in Continuous Environments (VLN-CE) requires an agent to follow natural language instructions through unseen environments. Ex
arXiv:2609.03199v1 Announce Type: new Abstract: Robot learning increasingly depends on broad and diverse demonstrations, yet collecting robot data remains expensive and poorly suited to covering the l
arXiv:2609.03475v1 Announce Type: new Abstract: Industrial inspection pipelines often restore a measured image before a detector acts on it, yet restoration can suppress detector-supported defect stru
arXiv:2506.10226v3 Announce Type: replace-cross Abstract: Synthetic data generation is increasingly used in machine learning for training and data augmentation. Yet, current strategies often rely on e
arXiv:2609.03820v1 Announce Type: cross Abstract: Long-video language models cannot look at every frame: an hour sampled once per second is 3,600 images, and a system keeps only a small fixed slice of
arXiv:2609.03695v1 Announce Type: new Abstract: Sign language dictionaries are essential resources for sign language learners, yet automatically retrieving a sign from a dictionary, given only a query
sounds like the government testing standard fail to adequately factor in monitorability. that’s bad. OpenAI announced its latest model, Astra today. When asked during a briefing if they followed the n
arXiv:2603.15834v2 Announce Type: replace-cross Abstract: We introduce a spectral hierarchy of cosmic-web classifications obtained by applying simple scale-weighting kernels to the density field befor
arXiv:2609.03215v1 Announce Type: new Abstract: Writing proficiency manifests in how students develop content, organize ideas, choose words, and use language. Despite growing interest in LLM-based stu
arXiv:2609.03586v1 Announce Type: new Abstract: Audio-video diffusion models rely on cross-modal attention to coordinate text, sound, and visual content, yet this same mechanism can introduce subtle a
arXiv:2609.04047v1 Announce Type: cross Abstract: Background: Researchers increasingly use repeated identical prompts to audit stochastic variation in large language model (LLM) brand recommendations,
⚠️ This is really scary. Proxies for OpenAI are laying the groundwork for saying the rest of us should suck up rogue AI risk and quit our bitching. Because they know they are on the verge of losing co
arXiv:2609.03383v1 Announce Type: new Abstract: Graph-based policy optimization improves credit assignment for long-horizon LLM agents by organizing rollout trajectories into state-transition graphs.
arXiv:2609.03704v1 Announce Type: new Abstract: This paper presents an integrated approach to modeling human competencies by combining the theoretical foundations of cognitive architectures with princ
arXiv:2609.03927v1 Announce Type: new Abstract: For robots to operate reliably in real-world environments, they need to perceive their surroundings, act, and reason about the consequences of those act
arXiv:2609.03561v1 Announce Type: new Abstract: Existing radar-LiDAR fusion methods rely on fixed residual weights, even though the informativeness of radar Doppler and LiDAR geometry is scan- and dir
arXiv:2609.03955v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially advanced code generation with large language models (LLMs) through executable feedback. The feedback for c
arXiv:2609.03729v1 Announce Type: new Abstract: Despite the remarkable prowess of Vision-Language Models (VLMs) in general multimodal tasks, they remain fundamentally ``flat'' when reasoning about the
arXiv:2510.20721v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly being adopted for tasks like drafting emails, summarizing meetings, and answering health questions. I
arXiv:2609.03681v1 Announce Type: new Abstract: Post-training VLA policies typically rely on supervised fine-tuning with costly expert demonstrations or reinforcement learning with expensive and poten
arXiv:2609.02107v1 Announce Type: cross Abstract: Discrete visual tokenization, predominantly driven by vector, scalar, and product quantization, lacks a unified conceptual framework for understanding
arXiv:2609.01902v1 Announce Type: cross Abstract: Assessments of cultural alignment have become an important part of the development and improvement of large language models (LLMs). However, the major
arXiv:2609.02042v1 Announce Type: new Abstract: Large language model (LLM) agents for long-horizon interactive tasks typically follow a ReAct-style protocol, issuing one primitive action per LLM round
arXiv:2410.15184v2 Announce Type: replace-cross Abstract: As trajectories sampled by policies used by reinforcement learning (RL) and generative flow networks (GFlowNets) grow longer, credit assignmen
arXiv:2609.02616v1 Announce Type: new Abstract: Emotion-driven image editing aims to evoke a specified target emotion by modifying emotion-relevant visual cues in a source image, while preserving the
arXiv:2609.01757v1 Announce Type: new Abstract: Vision-Language Pretrained Models (VLPMs) offer a scalable path to open-vocabulary chest radiology understanding, yet two aspects remain underexplored:
Anyone who cared about the science of AI would find this interesting. But if you are just here for the religion, I guess you don’t? 🚨Breaking: The success of GPT-6 Astra on ARC-AGI-3 provides strong e
arXiv:2604.07119v2 Announce Type: replace Abstract: Peer review plays a central role in the NLP publication process, but is susceptible to various biases. Here, we study language-of-study (LoS) bias:
Artificial intelligence security startup HiddenLayer Inc. today announced a 100 million Series B round, and a separate 27 million Series A went to edge security company Huskeys Security Ltd. Austin-ba
arXiv:2609.02748v1 Announce Type: new Abstract: Natural images follow a 1/f^2 spectral distribution: most signal energy lies in the low spatial frequencies, while the perceptually important structures
arXiv:2609.02152v1 Announce Type: cross Abstract: Multimodal Recommender Systems (MRSs) typically rely on a flawed 'modality harmony' assumption, presuming that multimodal features are inherently bene
arXiv:2609.02092v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) are increasingly considered for high-stakes decision-making, yet outcome-based fairness audits can miss where risks
arXiv:2609.02172v1 Announce Type: new Abstract: Optimization-based jailbreak attacks such as Greedy Coordinate Gradient (GCG) achieve strong effectiveness and transferability by optimizing adversarial
Brilliant paper on long-horizon agents. They cut 78.9% of an agent's LLM calls while raising its success rate. Here is how: It turns out that ReAct issues one primitive action per model round. That al
arXiv:2609.02401v1 Announce Type: new Abstract: Autoregressive vision language models unify heterogeneous perception tasks but are highly susceptible to compounding errors. On-policy distillation (OPD
arXiv:2601.05520v2 Announce Type: replace Abstract: Despite strong performance on many tasks, large language models (LLMs) show limited ability in historical and cultural reasoning, particularly in no