Knowledge catalogue
arXiv:2405.00636v4 Announce Type: replace-cross Abstract: This study investigates the robustness of shallow graph embedding methods for community detection in the face of network perturbations, specif
arXiv:2609.09507v1 Announce Type: new Abstract: Learned image matching has experienced significant progress in recent years, culminating in robust and accurate matchers such as RoMa, whose robustness
arXiv:2609.10395v1 Announce Type: new Abstract: This paper describes the Rosetta system for Subtask 1 (Context-Aware English-to-Dialectal Arabic Dialogue Translation) of the AlexandriaX shared task, p
arXiv:2609.09606v1 Announce Type: new Abstract: Neural radiance fields (NeRFs) and 3D Gaussian Splatting (3DGS) encode a scene with complementary inductive biases, but existing cross-representation di
arXiv:2609.08115v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) pretraining relies on an auxiliary load-balancing loss (LBL) to drive per-expert utilization toward uniformity. Post-training i
I am just sharing my config for Qwen 3.8 27b that fits on a 5060TI, what is cool about this is that you can even get vision! and a 85K context (I have 1.5gb of headroom for more context or a better qu
arXiv:2609.09852v1 Announce Type: new Abstract: The advance of multimodal large language models (MLLMs) has fundamentally reshaped the paradigm of human-computer interaction, especially speech interac
arXiv:2609.10125v1 Announce Type: new Abstract: Trochlear dysplasia (TD) is an abnormality of the femoral trochlea associated with anterior knee pain and patellar instability. The sulcus angle (SA) is
arXiv:2609.08175v1 Announce Type: new Abstract: Harness self-evolution is the process by which an agent modifies its prompts, tools, code, or orchestration in response to task feedback while keeping t
arXiv:2502.14043v3 Announce Type: replace Abstract: Most learning algorithms with formal regret guarantees essentially rely on trying all possible behaviors, which is problematic when some errors cann
arXiv:2601.09721v2 Announce Type: replace-cross Abstract: Consumer artificial intelligence chatbots are now accessed by hundreds of millions of users seeking health information, yet systematic evaluat
arXiv:2609.06611v1 Announce Type: cross Abstract: Assessing the literary quality of narratives requires evaluating interpretive dimensions (cultural representation, emotional depth, and philosophical
arXiv:2609.09999v1 Announce Type: new Abstract: Terminology-aware translation asks for more than a correct translation: the output must use the exact terms a glossary prescribes. The standard recipe,
arXiv:2609.08515v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into human society, aligning them with pluralistic social values has become a critical pri
Same weights. 50 of harness search. 3x on Terminal-Bench. We optimized the OpenCode harness for GPT-OSS-20B (high reasoning) with a meta-harness: an agent that reads failures, patches the harness, and
arXiv:2609.06124v1 Announce Type: new Abstract: High-quality multi-turn tool-use data is essential for training agentic models, yet existing data synthesis methods often underrepresent the argument-le
arXiv:2609.05511v1 Announce Type: new Abstract: Web agents need to navigate visually rich, long-horizon interfaces that change across sites, yet most previous agents still learn each task in isolation
arXiv:2609.09716v1 Announce Type: new Abstract: Customers rely on specific product attributes to compare products and make purchasing decisions, but e-commerce catalogs are messy and unstructured, mak
arXiv:2609.09240v1 Announce Type: new Abstract: Ultra-low-bit language models promise reductions in storage and memory traffic, but a nominal '1.58-bit' label does not specify the deployed representat
arXiv:2609.09432v1 Announce Type: new Abstract: Real-world datasets often exhibit evolving distributions, known as concept drift. Ignoring drift degrades predictive performance, while reliance on fixe
arXiv:2609.10363v1 Announce Type: new Abstract: SceneHI is a framework that lifts high-resolution, illumination-aware priors from 2D diffusion models to perform 3D texture synthesis. It is the first t
arXiv:2609.08126v1 Announce Type: new Abstract: We study scheming in LLM agents, in which agents covertly pursue misaligned goals. Our focus is to understand how scheming arises from the interaction o
arXiv:2609.05505v1 Announce Type: new Abstract: Systematic reviews require sustained human judgment across thousands of records, yet existing evaluations of large language models (LLMs) typically exam
arXiv:2609.06192v1 Announce Type: new Abstract: Scientific coding agents produce interdependent code, results, figures, and claims, yet evaluating final outputs alone does not establish whether their
arXiv:2609.10156v1 Announce Type: new Abstract: Small object detection in unmanned aerial vehicle (UAV) and remote sensing imagery requires preserving high-resolution detail while modeling long-range
arXiv:2609.07559v1 Announce Type: new Abstract: How do you validate a cheap, deterministic proxy for an oracle that is expensive, rate-limited, and non-stationary? We present a protocol built on adver
arXiv:2609.06226v1 Announce Type: cross Abstract: Large language models (LLMs) have recently made substantial progress in formal proof generation, yet presenting distinctive challenges in cryptographi
arXiv:2609.06149v1 Announce Type: cross Abstract: Script-based malware remains a prevalent attack technique. These scripts often contain indicators of compromise (IOCs) that provide actionable threat
arXiv:2609.08228v1 Announce Type: new Abstract: Modern LLM agents increasingly rely on reusable skills, yet as skill libraries scale to thousands of entries, effective retrieval becomes a bottleneck.
arXiv:2609.09672v1 Announce Type: new Abstract: The rapid advancement of audio and multimodal large language models has unlocked transformative speech understanding capabilities, yet evaluation framew
arXiv:2609.10382v1 Announce Type: cross Abstract: Finding new physics (NP) is the most important problem in particle physics today. Studying ``anomalies'', i.e., measurements of low-energy observables
Artificial intelligence is making companies into factories of intelligence. As AI becomes a new workload, it has also become a new attack surface. The factory model that enterprises are building to pr
arXiv:2601.17228v2 Announce Type: replace Abstract: Deep learning models in computational pathology often fail to generalize across cohorts and institutions due to domain shift. Existing approaches ei
arXiv:2609.10464v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architecture (JEPA) world models learn a compact latent representation of the world that supports prediction and planning,
arXiv:2609.08443v1 Announce Type: cross Abstract: Modeling long-term user behavior is central to sequential recommendation and billion-scale industrial recommender systems, yet production ranking mode
arXiv:2609.06647v1 Announce Type: new Abstract: Although professional workflows leverage large language models widely, the interpretation for auditing unconstrained free-text generation is usually int
arXiv:2609.09682v1 Announce Type: new Abstract: Many learning systems return a single point estimate even when admissible outputs form disconnected or non-convex sets. Under squared loss, an ambiguous
arXiv:2609.10376v1 Announce Type: new Abstract: Sparse-view X-ray 3D reconstruction is essential for reducing radiation exposure, but recovering a density field from a handful of X-ray projections is
arXiv:2609.10522v1 Announce Type: cross Abstract: Foundation vision-language models (VLMs) exhibit broad intelligence about the world, yet translating this intelligence into robot control remains chal
arXiv:2609.06271v1 Announce Type: cross Abstract: Some low-cost Internet of Things (IoT) sensor deployments lack device-level source authentication, leaving them vulnerable to impersonation or injecte
arXiv:2609.08789v1 Announce Type: cross Abstract: Frontier AI developers publish safety frameworks that commit them to evidencing whether their models are dangerous. The European Union and California
arXiv:2604.04925v3 Announce Type: replace Abstract: Generating procedural synthetic data for multi-view stereo (MVS) usually requires writing complex rules to match the realism of curated datasets. We
arXiv:2609.06740v1 Announce Type: new Abstract: Smart agriculture platforms usually bundle AI diagnosis, IoT sensing and decision push into a single package, so the green benefit attributable to each
Manufacturing floors, warehouses and production lines rarely stay fixed — tasks change, layouts shift and new products arrive, and most robots can’t keep up without significant reprogramming. Skild AI
arXiv:2609.08944v1 Announce Type: new Abstract: Agent skills provide a lightweight way to equip frozen language-model agents with domain knowledge and procedural guidance, yet obtaining high-quality s
arXiv:2609.07255v1 Announce Type: new Abstract: Language-model agents increasingly rely on skills: reusable procedural knowledge for reasoning, tool use, and interaction. Existing work studies how ski
arXiv:2609.06052v1 Announce Type: cross Abstract: Autonomous agent systems increasingly depend on reusable skill abstractions for consolidating experiential knowledge and domain expertise. These artif
arXiv:2609.09832v1 Announce Type: new Abstract: Recent advances in high-resolution fluorescence and electron microscopy have enabled nanoscale imaging across increasingly large brain volumes, but the
arXiv:2609.06835v1 Announce Type: cross Abstract: Agentic AI systems execute complex tasks through long-horizon workflows of planning, tool use, and multi-agent coordination. Task failures in these sy
arXiv:2609.09764v1 Announce Type: new Abstract: Social intelligence enables agents to read social context, infer intent, and adapt over sustained dialogue. As language models become autonomous collabo
arXiv:2609.05928v1 Announce Type: cross Abstract: Large language models now compute correct tax liabilities on over 90% of well-formed cases in statutory benchmarks, which makes them candidates for th
Bloomberg: Sources: Alibaba is set to lead a 300M round in AI model testing startup UniPat AI at a 2.5B valuation; UniPat founder Li Kuan worked at Alibaba's Tongyi Lab — Alibaba Group Holding Ltd. is
Maxwell Zeff / Wired: Sources: OpenAI asked members of Congress for guidance on whether orchestrating an industry-wide slowdown in AI development would be legal under antitrust law — Substantive coord
Bloomberg: Sources: Sam Altman told OpenAI employees that the company is considering slowing cutting-edge AI development, and he hopes other AI companies will do the same — OpenAI is considering slowi
arXiv:2609.08003v1 Announce Type: new Abstract: Behavioral foundation models have been proposed as stand-ins for human participants across settings, but it is unclear whether theories discovered on th
arXiv:2609.09159v1 Announce Type: new Abstract: The topological gap Delta -- the excess H_1 total persistence of a critical point cloud over a density-matched null -- scales as Delta sim L^{d+eta}. We
arXiv:2609.05800v1 Announce Type: new Abstract: Activation steering controls LLM behavior at inference time by adding learned directions to hidden states, but existing methods handle one concept at a
arXiv:2609.10356v1 Announce Type: new Abstract: Long-term change understanding from images of the same place revisited over time is a challenging task with applications in map maintenance and urban in
arXiv:2609.08950v1 Announce Type: cross Abstract: Text-to-SQL systems translate natural language queries into executable SQL, democratizing access to structured data. Despite recent advances driven by
arXiv:2609.06540v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in safety-critical applications, yet jailbreak attacks can conceal harmful intent through role-