Knowledge catalogue
arXiv:2509.05291v2 Announce Type: replace-cross Abstract: Large language models (LLMs) learn non-trivial abstractions during pretraining, such as detecting irregular plural noun subjects. However, bec
arXiv:2604.27977v1 Announce Type: new Abstract: Despite recent progress in language models and agents for scientific data-driven discovery, further advancing their capabilities is held back by the abs
arXiv:2604.28176v1 Announce Type: cross Abstract: Machine learning models can learn from data samples to carry out various tasks efficiently. When data samples are adversarially manipulated, such as b
arXiv:2604.27085v1 Announce Type: cross Abstract: Fine-tuning Large Language Models (LLMs) on consumer-grade GPUs is highly cost-effective, yet constrained by limited GPU memory and slow PCIe intercon
This discussion thread covers how to adjust temperature parameters in Ollama, the local language model platform. The post likely addresses configuration methods for controlling model sampling temperat
arXiv:2604.27335v1 Announce Type: new Abstract: Web filtering systems rely on accurate web content classification to block cyber threats, prevent data exfiltration, and ensure compliance. However, cla
arXiv:2604.27052v1 Announce Type: cross Abstract: Nonlinear models and optimization methods have successfully tackled a rapidly growing set of problems in recent years. Indeed, a relatively small tool
arXiv:2604.27374v1 Announce Type: new Abstract: As LLMs become credible readers of earnings calls, investor-relations Q&A, guidance, and disclosure language, supervised financial NLP benchmarks increa
arXiv:2504.15564v3 Announce Type: replace-cross Abstract: Existing class-level code generation datasets are either synthetic (ClassEval: 100 classes) or insufficient in scale for modern training needs
arXiv:2604.27201v1 Announce Type: cross Abstract: Hybrid-thinking language models expose explicit think and no-think modes, but current designs do not separate them cleanly. Even in no-think mode, mod
arXiv:2604.27721v1 Announce Type: cross Abstract: This paper presents a physically-informed fuzzy clustering of vertical sounding ionograms for automatically separating the ionogram into tracks suitab
arXiv:2508.21787v2 Announce Type: replace-cross Abstract: Best-of-n sampling improves the accuracy of large language models (LLMs) and large reasoning models (LRMs) by generating multiple candidate so
arXiv:2502.14270v3 Announce Type: replace Abstract: Birth weight serves as a fundamental indicator of neonatal health, closely linked to both early medical interventions and long-term developmental ri
arXiv:2602.07408v2 Announce Type: replace Abstract: Predicting gene regulation responses to biological perturbations requires reasoning about underlying biological causalities. While large language mo
arXiv:2505.19630v4 Announce Type: replace Abstract: Large language models (LLMs) struggle in real-world clinical consultations. Single-turn consultation systems require patients to describe all sympto
arXiv:2604.27559v1 Announce Type: cross Abstract: Radiology report generation (RRG) has emerged as a promising approach to alleviate radiologists' workload and reduce human errors by automatically gen
arXiv:2604.27555v1 Announce Type: new Abstract: Automatically generating interactive 3D indoor scenes from natural language is crucial for virtual reality, gaming, and embodied AI. However, existing L
arXiv:2604.27326v1 Announce Type: cross Abstract: Hyperspectral image super-resolution is essential for enhancing the spatial fidelity of HSI data, yet existing deep learning methods often struggle wi
arXiv:2604.27789v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used as core dependencies in software systems. However, the hosted LLM services evolve continuously thro
arXiv:2604.27217v1 Announce Type: new Abstract: Cognitive decline is highly heterogeneous across individuals, which complicates prognosis, trial design, and treatment planning. We present the Personal
arXiv:2602.21361v3 Announce Type: replace-cross Abstract: Ptychographic imaging at synchrotron and XFEL sources requires dense overlapping scans, limiting throughput and increasing dose. Extending coh
arXiv:2604.27861v1 Announce Type: cross Abstract: Decompositional jailbreaks pose a critical threat to large language models (LLMs) by allowing adversaries to fragment a malicious objective into a seq
arXiv:2604.27491v1 Announce Type: new Abstract: Modeling 4D human-object interaction (HOI) is a compelling challenge in computer vision and an essential technology powering virtual and mixed-reality a
arXiv:2601.08611v2 Announce Type: replace-cross Abstract: The growing scale of online misinformation urgently demands Automated Fact-Checking (AFC). Existing benchmarks for evaluating AFC systems, how
arXiv:2502.02097v3 Announce Type: replace Abstract: This aims to develop and validate a deep learning model that can accurately locate vertebral landmarks in lateral spine Dual energy X-ray Absorptiom
arXiv:2602.23163v3 Announce Type: replace Abstract: Large language models are beginning to show steganographic capabilities. Such capabilities could allow misaligned models to evade oversight mechanis
arXiv:2603.13589v2 Announce Type: replace-cross Abstract: Estimating motion from spatiotemporal geoscientific data is a fundamental component of many environmental modeling and forecasting tasks. In t
arXiv:2601.13969v2 Announce Type: replace Abstract: Retrieving evidence for language model queries from knowledge graphs requires balancing broad search across the graph with multi-hop traversal to fo
arXiv:2604.26820v1 Announce Type: new Abstract: Detectors often suffer from degraded performance, primarily due to the distributional gap between the source and target domains. This issue is especiall
arXiv:2604.26232v1 Announce Type: cross Abstract: Controllable medical video generation has achieved remarkable progress, but it still lacks interpretability, which requires the alignment of generated
arXiv:2604.26857v1 Announce Type: new Abstract: Deploying accurate object detection for Vulnerable Road User (VRU) safety on edge hardware requires balancing model capacity against computational const
arXiv:2604.26219v1 Announce Type: cross Abstract: The security of open-source software repositories is increasingly threatened by next-gen software supply chain attacks. These attacks include multipha
arXiv:2604.26488v1 Announce Type: new Abstract: One of the most exciting applications of vision models involve pixel-level reasoning. Despite the abundance of vision foundation models, we still lack r
arXiv:2604.26671v1 Announce Type: cross Abstract: Trust in clinical artificial intelligence (AI) cannot be reduced to model accuracy, fluency of generation, or overall positive user impression. In med
arXiv:2604.26733v1 Announce Type: new Abstract: Live future prediction refers to the task of making predictions about real-world events before they unfold. This task is increasingly studied using larg
arXiv:2604.26880v1 Announce Type: new Abstract: Patient portals now give individuals direct access to their electronic health records (EHRs), yet access alone does not ensure patients understand or ac
arXiv:2604.26568v1 Announce Type: new Abstract: Speech Sound Disorders (SSD) affect roughly five percent of children, yet speech-language pathologists face severe staffing shortages and unmanageable c
arXiv:2604.26456v1 Announce Type: cross Abstract: The digitisation of classical Sanskrit literature is impeded by a scarcity of annotated resources, particularly for Named Entity Recognition. While re
arXiv:2604.26070v1 Announce Type: new Abstract: Causal inference in continuous-time sequential decision problems is challenged by hidden confounders. We show that, in latent state-space models with ti
arXiv:2604.26211v1 Announce Type: new Abstract: In order to automate AI research we introduce a full, end-to-end framework, OMEGA: Optimizing Machine learning by Evaluating Generated Algorithms, that
arXiv:2604.25921v1 Announce Type: new Abstract: Large Language Models (LLMs) are trained to refuse harmful requests, yet they remain vulnerable to jailbreak attacks that exploit weaknesses in conversa
arXiv:2604.26675v1 Announce Type: cross Abstract: We investigate variational quantum classifiers (VQCs) for land-cover classification from multispectral satellite imagery, adopting a feature-map persp
This post compares Pi and Qwen 3.6 AI models to Tesla's Full Self-Driving (FSD) technology, suggesting that advanced local AI models enable autonomous computing capabilities similar to self-driving ve
arXiv:2604.26834v1 Announce Type: cross Abstract: We present a quantum feature-selection framework based on a higher-order unconstrained binary optimization (HUBO) formulation that explicitly incorpor
arXiv:2604.26506v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly integrated into academic peer review, their vulnerability to adversarial prompts -- adversarial instruc
arXiv:2604.25937v1 Announce Type: cross Abstract: Recent advancements in Text-to-Song generation have enabled realistic musical content production, yet existing evaluation benchmarks lack the professi
arXiv:2604.25925v1 Announce Type: new Abstract: Autoregressive language models suffer from high inference latency due to their sequential decoding nature. Speculative decoding (SD) mitigates this by e
arXiv:2604.26243v1 Announce Type: cross Abstract: Achieving realistic human-like conversation for virtual characters requires not only a simple memorization and recall of past events, but also the str
arXiv:2604.26167v1 Announce Type: cross Abstract: Recent work has shown that a model's input word embeddings can serve as effective control variables for steering its behavior toward outputs that sati
arXiv:2506.16742v3 Announce Type: replace Abstract: To be adopted in safety-critical domains like medical image analysis, AI systems must provide human-interpretable decisions. Variational Information
We've partnered with @OpenAI to offer GPT-5.5 in Devin at 50% off through May 14 starting today. GPT-5.5 is now available in Devin as an Agent Preview! GPT-5.5 has set a new bar for what's possible wi
arXiv:2604.25489v1 Announce Type: cross Abstract: Coherent transition radiation (CTR) spectroscopy is a critical diagnostic for characterizing the longitudinal structure of relativistic electron bunch
As AI models grow larger and more capable, the computational cost and time required to evaluate them has become a significant limiting factor in development, potentially surpassing training compute as
arXiv:2411.05174v2 Announce Type: replace Abstract: We consider the problem of estimating the transition dynamics T^* from near-optimal expert trajectories in the context of offline model-based reinfo
arXiv:2604.25700v1 Announce Type: cross Abstract: Software quality assurance remains a major challenge in industrial environments, where large-scale and long-lived systems inevitably accumulate defect
arXiv:2604.24935v1 Announce Type: cross Abstract: The Controller Area Network (CAN) is a safety-critical in-vehicle communication protocol that lacks built-in security mechanisms, making intrusion det
arXiv:2604.25774v1 Announce Type: new Abstract: Accurate nutrient estimation from unstructured recipe text is an important yet challenging problem in dietary monitoring, due to ambiguous ingredient te
arXiv:2505.14174v2 Announce Type: replace Abstract: LLMs are effective at code generation tasks like text-to-SQL, but is it worth the cost? Many state-of-the-art approaches use non-task-specific LLM t
DeepAgents Deploy is great, you get - a fully open agent harness (no hidden stuff, inspect everything) - managed infra - can use any cocktail of models including Open Models - and everything is traced
arXiv:2604.25319v1 Announce Type: new Abstract: The exponential surge in high-resolution remote sensing data faces a severe bottleneck in satellite-to-ground transmission. Limited downlink bandwidth f