Knowledge catalogue
arXiv:2606.20711v1 Announce Type: new Abstract: UI videos provide a natural input for generating interactive webpages, as they capture both webpage appearance and action-triggered state transitions. H
arXiv:2606.23327v1 Announce Type: new Abstract: Video editing has become essential in digital media creation, yet existing automated systems are restricted to short segment processing and domain-speci
arXiv:2606.21386v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) achieve state-of-the-art performance on many robotic manipulation tasks, yet they can still behave unpredictably
arXiv:2606.23062v1 Announce Type: cross Abstract: We introduce VolHuMe, a dataset of high-quality 4D human scans captured with a state-of-the-art volumetric studio using 64 RGB and 32 depth cameras. V
arXiv:2606.21600v1 Announce Type: new Abstract: Multi-task robot manipulation policies are challenging to learn from demonstration because traditionally a single network must select among qualitativel
arXiv:2606.20728v1 Announce Type: new Abstract: Vision foundation tools such as open-vocabulary detectors, segmentation models, and post-processing operators are powerful building blocks for computer
arXiv:2603.06445v2 Announce Type: replace Abstract: Situated reasoning often relies on active exploration, yet in many real-world scenarios such exploration is infeasible due to physical constraints o
arXiv:2606.22079v1 Announce Type: cross Abstract: Web data curation has been widely studied for decoder Large Language Model (LLM) pretraining. Encoders for dense-terminology domains such as medicine,
arXiv:2606.20781v1 Announce Type: cross Abstract: World Action Models (WAMs) are embodied predictive-action models that make a forecast of the future available to action. Recent WAMs repurpose large v
arXiv:2606.21861v1 Announce Type: new Abstract: Automated classroom engagement recognition holds substantial promise for scalable learning analytics, yet the suitability of modern Vision-Language Mode
The advanced civilizations of sci-fi legend (Banks, Asimov, etc) have some form of simulation to guide society. @joon_s_pk is taking a crack at building that simulator with @simile_ai. As Joon's cofou
sqlite-utils is my combined Python library and CLI tool for working with SQLite databases. It provides an extensive set of higher-level operations on top of Python's default sqlite3 package, including
CyberAgent reports about 2,000 internal Claude Code users and describes its governance, training and software-delivery operating model; no measured outcome is published.
arXiv:2606.12040v1 Announce Type: new Abstract: The design of reinforced concrete highway barriers is a safety-critical process that requires strict compliance with regulatory provisions such as the A
arXiv:2606.11419v1 Announce Type: new Abstract: Most existing drone-based inspection systems require the drone to fly dangerously close to the target or follow complex flight paths to capture small de
arXiv:2509.11575v3 Announce Type: replace Abstract: Time series reasoning treats time as a first-class axis and incorporates intermediate evidence directly into the answer. This survey defines the pro
arXiv:2606.12218v1 Announce Type: cross Abstract: Understanding spatial distribution of fallow land is important for optimizing the food-water (FW) nexus, given fallowing's role in crop rotation and w
arXiv:2606.11615v1 Announce Type: new Abstract: The widespread adoption of face recognition (FR) technologies raises serious privacy concerns, as facial data can be exploited without consent. To addre
arXiv:2606.12126v1 Announce Type: new Abstract: Existing computational pathology methods predominantly operate within whole-slide image (WSI)-level multiple instance learning (MIL) paradigms, while pa
arXiv:2606.12003v1 Announce Type: new Abstract: Self-consistency improves LLM reasoning by sampling multiple outputs and selecting the most consistent answer, but existing formulations largely rely on
arXiv:2606.12342v1 Announce Type: cross Abstract: Domain fine-tuning degrades the safety of large language models: fine-tuned specialists readily comply with harmful prompts framed in domain language.
arXiv:2606.12226v1 Announce Type: new Abstract: While deep learning has significantly advanced image reconstruction of Electrical Capacitance Tomography (ECT), most data-driven methods map directly be
arXiv:2606.11910v1 Announce Type: new Abstract: Traffic law liability determination is critical for assigning legal penalties, requiring the simultaneous identification of interdependent statutory pro
arXiv:2601.10774v2 Announce Type: replace Abstract: A key challenge in normalizing flows is finding expressive invertible scalar bijections. Existing approaches face trade-offs: affine transformations
arXiv:2606.11751v1 Announce Type: cross Abstract: Multi-turn image editing is essential for iterative design, yet current models often struggle with identity drift and error accumulation over successi
arXiv:2606.11553v1 Announce Type: new Abstract: Generic time-series foundation models transfer poorly to wireless network telemetry whose signals are bursty, zero-inflated, and coupled across protocol
arXiv:2606.12386v1 Announce Type: cross Abstract: Advancing scientific understanding through mechanistic modeling requires posing the right experimental questions to yield maximally informative data.
arXiv:2606.12113v1 Announce Type: cross Abstract: Transformer-based language models for SMILES strings suffer from a locality gap: standard character-level tokenization fragments chemically meaningful
arXiv:2606.11874v1 Announce Type: new Abstract: With the development of autonomous driving systems, mining high-value, safety-critical, and planning-relevant scenarios from large-scale driving logs ha
arXiv:2405.06995v4 Announce Type: replace-cross Abstract: Automated deception detection is crucial for assisting humans in accurately assessing truthfulness and identifying deceptive behavior. Convent
arXiv:2606.11213v1 Announce Type: new Abstract: We present Context Window Lifecycle (CWL), a context-management scheme that gives long-horizon LLM agents an effectively unbounded working horizon. As a
arXiv:2408.02600v3 Announce Type: replace Abstract: Background. Biomedical language models should improve performance on biomedical text while retaining general-language-modeling fluency. For Mamba-ba
arXiv:2606.11482v1 Announce Type: cross Abstract: Understanding and predicting how social beliefs evolve in response to events -- from policy changes to scientific breakthroughs -- remains a fundament
arXiv:2510.07750v3 Announce Type: replace-cross Abstract: Robust optimization safeguards decisions against uncertainty by optimizing against worst-case scenarios, yet their effectiveness hinges on a p
arXiv:2606.12075v1 Announce Type: cross Abstract: Network Intrusion Detection Systems (NIDS) heavily utlize Machine Learning (ML) but ML models can be manipulated via adversarial attacks. These attack
arXiv:2606.12281v1 Announce Type: cross Abstract: In Decentralized Training and Decentralized Execution (DTDE) for cooperative Multi-Agent Reinforcement Learning (MARL), action-advising-based knowledg
arXiv:2510.03520v2 Announce Type: replace-cross Abstract: Ensuring safety is a foundational requirement for large language models (LLMs). Achieving an appropriate balance between enhancing the utility
arXiv:2606.11569v1 Announce Type: cross Abstract: Closed-loop planning in complex, real-world driving scenarios presents a critical challenge for autonomous driving systems. While traditional rule-bas
arXiv:2606.11925v1 Announce Type: new Abstract: Sign language translation (SLT) converts sign language video into spoken language text and holds significant promise for improving accessibility and ena
arXiv:2603.20190v2 Announce Type: replace Abstract: Composed Video Retrieval (CoVR) aims to find a target video given a reference video and a textual modification. Prior work assumes the modification
arXiv:2606.11891v1 Announce Type: cross Abstract: Multi-objective reinforcement learning for humanoid robots must coordinate locomotion and manipulation within a single policy. A natural design choice
arXiv:2510.17816v2 Announce Type: replace-cross Abstract: Wi-Fi-based human activity recognition (HAR) provides substantial convenience and has emerged as a thriving research field, yet the coarse spa
arXiv:2506.20040v3 Announce Type: replace-cross Abstract: Interpreting language models remains challenging due to the existence of residual stream, which linearly mixes and duplicates features across
arXiv:2606.11473v1 Announce Type: cross Abstract: Prior-fitted networks (PFNs) are a promising class of tabular foundation models that perform in-context learning, whereby the entire labelled training
arXiv:2606.11952v1 Announce Type: new Abstract: This paper introduces a novel tactile sensor for in-hand manipulation with slip-aware control that integrates velocity, force/torque, and pressure map s
arXiv:2606.11616v1 Announce Type: new Abstract: High-quality training data is essential for the success of machine learning models. However, real-world datasets often contain mixed types of errors ari
arXiv:2606.11835v1 Announce Type: cross Abstract: Collecting participants' lived experiences is central to design research. Focus groups are uniquely valuable because participants not only share indiv
arXiv:2602.18291v2 Announce Type: replace Abstract: Online Multi-Agent Reinforcement Learning (MARL) is a prominent framework for efficient agent coordination. Crucially, enhancing policy expressivene
arXiv:2603.09715v2 Announce Type: replace Abstract: Visual instruction tuning is crucial for improving vision-language large models (VLLMs). However, many samples can be solved via linguistic patterns
arXiv:2606.11687v1 Announce Type: new Abstract: Unmanned Aerial Vehicle (UAV) threats have emerged as a defining security challenge of the 21st century. This paper presents DroneShield-AI, a unified o
arXiv:2606.11648v1 Announce Type: cross Abstract: Backdoor attacks pose a serious threat to the safety and reliability of Large Language Models (LLMs), as they cause models to behave normally on clean
arXiv:2606.11901v1 Announce Type: cross Abstract: Bimanual robot systems substantially expand manipulation capabilities, but coordinating two arms introduces additional control complexity and failure
arXiv:2606.11408v1 Announce Type: new Abstract: Action chunking has become a standard design in modern robot policies, from diffusion/flow policies to vision-language-action models, where the policy p
arXiv:2606.11324v1 Announce Type: cross Abstract: We introduce Embodied-R1.5, a unified Embodied Foundation Model (EFM) that integrates comprehensive embodied reasoning capabilities, spanning embodied
arXiv:2606.11555v1 Announce Type: cross Abstract: The escalating demand for mental healthcare, driven by rising societal stress, highlights the limitations of traditional psychiatric diagnostics. Conv
arXiv:2606.11976v1 Announce Type: cross Abstract: Software engineering tools increasingly rely on LLM based agents to localize files to change to resolve a software issue. Most AI agents explore repos
arXiv:2606.11806v1 Announce Type: new Abstract: Production LLM systems accumulate reusable operational experience, but the practical deployment issue is not merely whether such experience can help. It
arXiv:2606.11620v1 Announce Type: cross Abstract: Approximate tensor-network simulators enable classical simulation of quantum circuits beyond the reach of exact methods, but selecting optimal approxi
arXiv:2603.08501v3 Announce Type: replace Abstract: Large language models (LLMs) can answer religious knowledge queries fluently, yet they often hallucinate and misattribute sources, which is especial
arXiv:2606.11272v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative and privacy-preserving model training across distributed clients, but most existing FL systems implicitl