Knowledge catalogue
arXiv:2607.03787v1 Announce Type: new Abstract: Accurately modeling biomolecular interactions is a central bottleneck in biology and therapeutic discovery. Here, we introduce Open Drug Discovery Engin
arXiv:2607.04096v1 Announce Type: new Abstract: Current agentic workflows usually involve decomposing user requests into sequences of tool calls with correctly resolved parameters, the results of whic
arXiv:2607.03394v1 Announce Type: new Abstract: Real time location data derived from mobile applications is a powerful tool for addressing various urban challenges, including tourism planning, parking
arXiv:2606.18089v2 Announce Type: replace Abstract: Post-training pipelines that combine supervised fine-tuning (SFT) with reinforcement learning (RL) have emerged as the key recipe for transforming l
arXiv:2607.02612v1 Announce Type: cross Abstract: Vision Transformers achieve strong image classification accuracy but process all image regions with nearly the same computation, even when many region
arXiv:2607.05241v1 Announce Type: new Abstract: Neuromorphic visuo-tactile sensing offers a promising paradigm for low-latency and low-power robotic perception. However, existing systems still rely he
Moving Beyond the Prototype The AI landscape has shifted. While 'vibe coding' with tools like Antigravity and AI Studio lets you build and deploy complex agents in minutes, the real work begins on 'Da
arXiv:2607.04613v1 Announce Type: new Abstract: Autonomous agents are moving from sandboxed text generators to operators of code, data, and physical infrastructure, and they increasingly learn while d
arXiv:2607.04845v1 Announce Type: cross Abstract: Quantum Architecture Search (QAS) automates the design of parameterized quantum circuits for variational quantum algorithms, yet existing benchmarks o
arXiv:2607.04241v1 Announce Type: cross Abstract: Plasma disruption is a critical threat to tokamak safety. Existing data-driven predictors mainly rely on time-series diagnostic signals, while visible
arXiv:2602.21009v2 Announce Type: replace-cross Abstract: Modern recommender systems leverage ultra-long user behavior sequences to capture dynamic preferences, but end-to-end modeling is infeasible i
arXiv:2607.02825v1 Announce Type: cross Abstract: We release extsc{JavaVulBench}, a benchmark dataset and evaluation harness for Java vulnerability detection. The dataset contains sim30{,}600 Java met
arXiv:2607.03166v1 Announce Type: cross Abstract: Template-based contrastive synthesis is scalable, but its candidates often differ only in a few entity-slots while sequence-level optimization spreads
arXiv:2607.03481v1 Announce Type: new Abstract: Modernizing cancer registries with deep learning is opening new opportunities to automate labor-intensive tasks such as the coding of pathology reports.
arXiv:2607.03651v1 Announce Type: new Abstract: While traditional hub capacity planning models optimize effectively for quantitative inputs, they often fail to digest qualitative business context. We
arXiv:2607.04907v1 Announce Type: new Abstract: Deploying Large Language Models (LLMs) in high-stakes clinical settings remains limited by structural hallucinations, weak deterministic reasoning over
arXiv:2607.03261v1 Announce Type: new Abstract: Recent large language models (LLMs) have demonstrated remarkable progress in 3D spatial reasoning, spatial grounding, and fine-grained geometric underst
arXiv:2607.02834v1 Announce Type: new Abstract: Molecular optimization often starts from a pretrained generative model that captures a broad prior over valid molecular structures. At test time, howeve
arXiv:2607.04846v1 Announce Type: cross Abstract: Transformers follow implicit curricula whereby some tasks are learned before others. However, how explicit pretraining curricula influence learning, g
arXiv:2607.03730v1 Announce Type: new Abstract: Conversational agents are increasingly embedded in human collaborative work, yet they remain fundamentally passive and reactive: they respond to explici
arXiv:2607.03502v1 Announce Type: cross Abstract: Frontier LLMs can perform multi-step reasoning over content-free filler tokens like dots or counting sequences, producing correct answers with no visi
arXiv:2607.04906v1 Announce Type: new Abstract: Under the Shipping 4.0 paradigm, autonomous and reduced-crew vessels require intelligent internal systems to maintain operational safety and structural
arXiv:2607.05353v1 Announce Type: cross Abstract: Watermarking methods embed imperceptible and verifiable signals into text generated by large language models (LLMs). Existing approaches include zero-
arXiv:2607.03103v1 Announce Type: cross Abstract: Clinical cardiac imaging pipelines currently deploy separate models for each dataset and modality, incurring redundant training costs and precluding k
arXiv:2607.03143v1 Announce Type: cross Abstract: Vision-language alignment powers open-vocabulary recognition, retrieval, and LVLM grounding, yet natural captions are often underspecified, making sim
arXiv:2606.22726v2 Announce Type: replace Abstract: Choreographic motion generation poses unique challenges for AI, demanding precise semantic control over complex, temporally structured, and expressi
arXiv:2607.03953v1 Announce Type: cross Abstract: This study independently replicates and extends the Natural Language Tools (NLT) framework of Johnson et al.~(2025), which questions the use of struct
arXiv:2607.05339v1 Announce Type: cross Abstract: Group Relative Policy Optimization (GRPO) is effective when the current policy already samples useful reasoning trajectories, but it stalls on hard pr
arXiv:2607.03321v1 Announce Type: new Abstract: Continuum manipulators mounted on multi-rotor UAVs enable compliant aerial manipulation, but payloads and propeller downwash amplify out-of-plane bendin
arXiv:2607.05277v1 Announce Type: cross Abstract: Defenses that provide security guarantees against prompt injection attacks rely on strict isolation between trusted instructions and untrusted data. I
The automotive industry is at a pivotal crossroads as it hits the gas on adopting new technology. The era of the traditional connected vehicle has shifted into the age of the software-defined vehicle
arXiv:2607.01639v1 Announce Type: new Abstract: Universal traffic laws describe recurrent patterns in congestion, mobility and driving behavior across cities, providing a scientific basis for transpor
arXiv:2607.01728v1 Announce Type: cross Abstract: Visual regression testing (VRT) is a standard quality assurance step in modern software release pipelines. On every change, it re-renders user interfa
arXiv:2607.02245v1 Announce Type: new Abstract: Mental health disorders affect nearly one billion people globally, yet 75% of individuals in low- and middle-income countries receive no treatment due t
arXiv:2607.02283v1 Announce Type: cross Abstract: In-context learning (ICL) operates via implicit gradient descent embedded in the forward pass of modern AI architectures -- Transformers, Mamba, state
arXiv:2607.01661v1 Announce Type: new Abstract: Multi-agent systems are increasingly used for forecasting future events, as deliberation among multiple LLMs is believed to improve reasoning and calibr
arXiv:2607.01362v1 Announce Type: cross Abstract: Quantum mechanical (QM) cluster models provide an effective framework for mechanistic studies of enzymatic reactions but remain computationally demand
arXiv:2607.02020v1 Announce Type: new Abstract: Multimodal large language models must continually adapt to evolving tasks and domains, yet standard continual learning metrics mainly measure whether ol
arXiv:2607.01365v1 Announce Type: cross Abstract: Given one or more images of a railway crossing, can we leverage visual cues that allow us to robustly estimate how safe it is? Can we improve our abil
arXiv:2607.01392v1 Announce Type: new Abstract: Aligning large language models with diverse and heterogeneous human values requires multi-objective alignment methods to effectively trade off conflicti
arXiv:2607.02032v1 Announce Type: new Abstract: Evaluating LLM agents on benchmarks like SWE-Bench and GAIA can be expensive, time-consuming, and requires complex infrastructure. A single evaluation c
arXiv:2512.03042v3 Announce Type: replace-cross Abstract: We introduce PPTArena, a benchmark for PowerPoint editing that evaluates how agents modify real slides from natural-language instructions. Unl
arXiv:2604.03497v2 Announce Type: replace-cross Abstract: Vision-language-model (VLM)-guided reinforcement learning (RL) has recently attracted significant attention for it, replacing brittle hand-cra
arXiv:2607.02363v1 Announce Type: cross Abstract: Quantum Fast-Weight Programmers (QFWPs) store temporal information in dynamically programmed variational-circuit parameters rather than in nonlinear r
arXiv:2607.02043v1 Announce Type: cross Abstract: Disaggregated LLM serving runs prefill and decode on separate GPU pools to keep the two phases from interfering. In practice, this creates a new asymm
arXiv:2607.00247v1 Announce Type: cross Abstract: Large audio-language models (LALMs) frequently hallucinate by overriding acoustic evidence with language priors. While contrastive decoding (CD) offer
arXiv:2607.01061v1 Announce Type: new Abstract: Computer-assisted synthesis planning breaks target molecules into accessible precursors using large libraries of reaction rules that assign each transfo
Bridgewater just published numbers that should make every frontier lab nervous. The world's largest hedge fund tested Gemini, Claude, and GPT on six document filtering tasks its investors do every day
arXiv:2607.00514v1 Announce Type: cross Abstract: Automatic understanding of dynamic 4D point clouds, the 3D-point sequences captured over time by depth sensors and LiDAR, is central to robotics and e
arXiv:2607.00766v1 Announce Type: new Abstract: Text-to-image personalization aims to generate a user-provided subject in novel scenes described by text. However, most existing methods encode subject
arXiv:2512.15702v2 Announce Type: replace Abstract: Autoregressive video diffusion models hold promise for world simulation but are vulnerable to exposure bias arising from the train-test mismatch. Wh
arXiv:2607.00162v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) reparameterizes weight updates in a fixed basis: low-rank adapters operate in the spatial domain, while a recent
Background Today, in coordination with the FBI, Lumen, and others, Google took action against the NetNut residential proxy network, also known as Popa. This action builds on our disruption of the IPID
arXiv:2607.00371v1 Announce Type: cross Abstract: Visual AutoRegressive modeling (VAR) has pioneered a coarse-to-fine multi-scale autoregressive generative paradigm, demonstrating strong capabilities
arXiv:2607.00902v1 Announce Type: new Abstract: Driven by Artificial Intelligence-Generated Content (AIGC), the authenticity of audio-visual content is facing severe challenges. Temporal Forgery Local
arXiv:2607.00832v1 Announce Type: cross Abstract: A single panorama captures the full visual sphere from one camera center, yet confines users to looking around in place without enabling true scene ex
arXiv:2607.00286v1 Announce Type: cross Abstract: Oscillatory neural networks (ONNs) have emerged as a promising neuromorphic architecture, leveraging coupled dynamical systems to perform computation
arXiv:2607.01105v1 Announce Type: new Abstract: We present SynLaD, a latent diffusion framework for small-molecule generation that unifies ligand-based drug design objectives (what to make) with synth
arXiv:2607.00351v1 Announce Type: new Abstract: Vision-Language-Action models excel at robotic manipulation, driven by the scale and diversity of demonstration data. However, standard training paradig
arXiv:2606.31763v1 Announce Type: new Abstract: Autonomous wet-lab experimentation requires more than plausible protocol text: biological intent, quantitative procedures, device constraints and experi