Knowledge catalogue
arXiv:2609.16625v1 Announce Type: cross Abstract: How and why does a recommender system fail the users it serves? Oftentimes, practitioners are left to improve their algorithms based on a combination
Banger report from Salesforce. Pretty interesting to see more of these custom enterprise models. Salesforce trained the enterprise agent model from the same files it uses to configure agents. Koa star
arXiv:2609.17065v1 Announce Type: cross Abstract: AI assistance places a metacognitive demand on users, who must judge their own competence and the system's. Yet designers lack comparative evidence on
arXiv:2609.15995v1 Announce Type: new Abstract: Emerging AI regulation mandates bias audits of high-risk systems, and audit scores are beginning to be used to rank models. Both uses assume different a
Hey experts! I genuinely have this question and would love a general consensus from people actually using these models. LLMs have advanced a lot in benchmarks and in practical usage. Even GPT-4o and G
arXiv:2609.16637v1 Announce Type: new Abstract: Efficient perception is central to robotic systems operating under constrained computation, memory, and latency budgets. Knowledge transfer from larger
arXiv:2609.16814v1 Announce Type: new Abstract: While Large Language Model (LLM)-based Natural Language Inference (NLI) systems achieve high accuracy, their decision-making processes lack auditable st
arXiv:2609.16341v1 Announce Type: new Abstract: Physical-layer key generation (PKG) enables wireless devices to establish shared keys from reciprocal channel observations without directly exchanging t
arXiv:2609.16096v1 Announce Type: cross Abstract: Large language model coding agents have recently become useful for software tasks, but weaker or open-weight agents still struggle to reliably interpr
arXiv:2609.17394v1 Announce Type: cross Abstract: Small differences on coding-agent leaderboards are often read as an ordering of systems. We audit whether the published verdicts support this reading,
arXiv:2609.16313v1 Announce Type: cross Abstract: In agentic distributed systems, an agent may be authorized to mutate external infrastructure while lacking evidence that the mutation is ready to exec
arXiv:2609.16032v1 Announce Type: cross Abstract: Diffusion-based artifact detectors score whole-slide image patches by reconstruction error under a model fine-tuned on clean tissue. We show that cond
arXiv:2609.16489v1 Announce Type: cross Abstract: Electrocardiogram (ECG) delineation identifies the boundaries of P waves, QRS complexes, and T waves, providing structural annotations that can guide
arXiv:2609.17464v1 Announce Type: cross Abstract: Multi-agent systems split a task across a tree of agents and justify the split with folklore: smaller contexts, cleaner separation, parallelism. We as
arXiv:2609.16907v1 Announce Type: cross Abstract: AI companions can provide meaningful relationships, yet these relationships remain vulnerable to platform-initiated changes. We study AI companion dis
arXiv:2609.16689v1 Announce Type: new Abstract: Large-scale vision-language models (VLM) such as CLIP enable strong open-vocabulary reasoning, yet deploying these capabilities on resource-constrained
arXiv:2609.16572v1 Announce Type: cross Abstract: Text-to-image diffusion models often use a fixed number of denoising steps, balancing time costs and image quality. However, the optimal number of ste
arXiv:2609.17398v1 Announce Type: new Abstract: This paper addresses the challenge of making complex healthcare information more accessible through automated Plain Language Adaptation (PLA). PLA aims
arXiv:2609.17291v1 Announce Type: new Abstract: The quest for new materials increasingly relies on predictive models and comprehensive simulations that span scales from atomic to macroscopic levels. H
arXiv:2603.16365v3 Announce Type: replace Abstract: We study alpha factor mining, the automated discovery of predictive signals from noisy, non-stationary market data-under a practical requirement tha
arXiv:2609.16378v1 Announce Type: cross Abstract: Digital twins provide a scalable and cost-effective complement to real-world testing for validating autonomous-driving and advanced driver-assistance
arXiv:2609.17221v1 Announce Type: cross Abstract: Autonomous Software Engineering Agents (SWE-Agents) excel in deterministic coding tasks but struggle with Architecture 0, the nascent system design ph
arXiv:2609.17168v1 Announce Type: cross Abstract: Autonomous systems require reliable place recognition for efficient and effective simultaneous localisation and mapping (SLAM). Traditional geometric
arXiv:2609.16207v1 Announce Type: new Abstract: Spatial Transcriptomics (ST) has transformed biomedical research by enabling the spatial mapping of gene expression across tissue sections. However, hig
arXiv:2609.16779v1 Announce Type: new Abstract: LLMs are increasingly employed in a wide range of decision-making tasks. However, the opacity of their internal reasoning makes it difficult to validate
arXiv:2609.16436v1 Announce Type: cross Abstract: Simulations based on large language models (LLMs) have proven to be powerful for understanding human behavior, making them valuable additions to the s
arXiv:2609.17124v1 Announce Type: new Abstract: Offshore maintenance requires operations in the air, the surface, and the subsea domain and include human supervision. This paper presents LOTUSim-Energ
arXiv:2609.16331v1 Announce Type: new Abstract: We present ManiSkillFormer, a neuro-symbolic framework for demonstration-free and compositional robotic manipulation. Instead of learning end-to-end vis
arXiv:2609.16934v1 Announce Type: new Abstract: Cranial implant generation is an important task in medical imaging. Recent point cloud based generative methods, particularly flow matching, offer stron
arXiv:2609.17524v1 Announce Type: new Abstract: World-action models (WAMs) jointly model future observations and actions, typically predicting the future as RGB images. Other visual modalities such as
arXiv:2609.15999v1 Announce Type: new Abstract: Accessing legal information in Nepal is difficult due to complex terminology, limited resources, and misinformation. We introduce an AI-powered legal as
arXiv:2609.17416v1 Announce Type: new Abstract: Voice agents built on LLMs follow a rigid listen-think-speak loop that inserts seconds of dead air before every reply. We show that continuous-time cogn
Nice work from Adobe. It's standard practice to store a fixed reference answer for every eval case. When the underlying data changes daily, that stored answer goes stale. Adobe researchers write each
arXiv:2609.17405v1 Announce Type: new Abstract: Legged robots offer a variety of automation applications in real-world scenarios. But areas that are difficult to traverse, like slopes, caves, or scaff
arXiv:2609.16995v1 Announce Type: new Abstract: Autoresearch agents are reshaping the research ecosystem, but they can also let flawed claims enter the literature at scale. Human advisors catch such i
arXiv:2505.13388v4 Announce Type: replace-cross Abstract: Reward models are essential for aligning language model outputs with human preferences, yet existing approaches often lack both controllabilit
arXiv:2609.17440v1 Announce Type: new Abstract: Optimizing industrial process flowsheets is often computationally prohibitive due to the high cost of rigorous simulations and the curse of dimensionali
arXiv:2510.09619v2 Announce Type: replace-cross Abstract: [Corrected v2: an audit found that the score, threshold, and latency descriptions below are not what the shared codebase implements, and that
arXiv:2603.02227v2 Announce Type: replace-cross Abstract: Learned gates can approximate sparse attention patterns on frozen transformers, yet provide limited benefit over random gates when trained joi
arXiv:2601.10511v2 Announce Type: replace-cross Abstract: Model counting of Disjunctive Normal Form (DNF) formulas is a critical problem in applications such as probabilistic inference and network rel
arXiv:2609.16071v1 Announce Type: cross Abstract: Cross-machine deployment of industrial world models requires transfer across changes in dynamics, sensing interfaces, sampling regimes, and control un
arXiv:2609.16804v1 Announce Type: cross Abstract: Time-series foundation models have demonstrated strong cross-domain transfer, yet their common architectural assumptions remain poorly aligned with we
arXiv:2609.15991v1 Announce Type: new Abstract: Standard subword tokenizers either treat every orthographic variation of a word (such as hello, Hello, HELLO, and Hello) as unrelated vocabulary entries
arXiv:2609.16745v1 Announce Type: cross Abstract: Action Chunking Transformers (ACT) are widely used to learn robot manipulation from demonstrations. Their conditional variational autoencoder includes
arXiv:2609.17198v1 Announce Type: new Abstract: Autonomous nano-UAV navigation requires accurate ego-motion estimation under stringent size, weight, power, and computing (SWaP-C) constraints, where vi
arXiv:2609.17427v1 Announce Type: cross Abstract: Real-time multi-object tracking systems remain highly vulnerable to full and long-term occlusion, where targets temporarily or completely disappear fr
arXiv:2609.16368v1 Announce Type: cross Abstract: Vision-language models (VLMs) can generate routes directly from aerial imagery for off-road navigation, but their predictions provide no indication of
arXiv:2609.16098v1 Announce Type: cross Abstract: Large Language Model (LLM) agents have demonstrated impressive capabilities across a variety of domains, particularly when integrated with external to
arXiv:2609.16933v1 Announce Type: cross Abstract: Modern predictive systems expose multiple quantities that are commonly interpreted as measures of confidence. However, these quantities can summarize
arXiv:2609.13171v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) use automatic differentiation to impose differential-equation residuals, but good agreement in function values
arXiv:2609.13170v1 Announce Type: cross Abstract: Blockchain-enabled Federated Learning (FL) marketplaces enable collaborative model training among mutually distrustful participants through smart cont
arXiv:2609.14178v1 Announce Type: new Abstract: The rapid diffusion of hate speech and misinformation on social networks challenges democratic societies, since direct suppression efforts may deepen po
arXiv:2603.11667v3 Announce Type: replace Abstract: This paper examines how value is constructed and negotiated in today's increasingly automated language and translation industry. Drawing on intervie
arXiv:2609.13840v1 Announce Type: new Abstract: A contract-logistics spare-parts operator is paid on order-level service: an order counts only if every requested line is fulfilled, yet forecasters are
Last year Ruxandra Teslo, a policy analyst who focuses on clinical trials, posted an idea for supercharging medical AI systems: Use data from failed biotech companies. By bidding at their bankruptcy p
arXiv:2603.19574v2 Announce Type: replace-cross Abstract: Conversational AI systems are increasingly used for personal reflection and emotional disclosure, raising concerns about their effects on vuln
arXiv:2609.14756v1 Announce Type: new Abstract: Reliable path tracking is crucial for autonomous underwater vehicles (AUVs) operating in dynamic and uncertain marine environments. However, traditional
arXiv:2609.15277v1 Announce Type: new Abstract: Entrepreneurial cognition is a foundation of entrepreneurship research. Yet the growing involvement of large language models (LLMs) in entrepreneurial w
arXiv:2609.14248v1 Announce Type: cross Abstract: Faithful citation attribution begins with identifying the intended source for a scientific claim. We study this source-identification capability throu
arXiv:2609.15523v1 Announce Type: cross Abstract: Logic attack graphs grounded in scanner output provide explicit and auditable attack path reasoning LLM-based agents lack. Integrating symbolic framew