Knowledge catalogue
arXiv:2608.06037v1 Announce Type: new Abstract: Relational inductive biases are essential for capturing structural dependencies among data. This study investigates a dual-level relational framework fo
arXiv:2510.05589v3 Announce Type: replace-cross Abstract: Effective time series forecasting enables various real-world applications, benefiting from the proliferation of mobile devices. However, the v
arXiv:2608.06364v1 Announce Type: cross Abstract: The use of e-commerce mobile applications is expanding in Nigeria, creating both opportunities and risks, including fraud and reduced user control ove
arXiv:2608.05424v1 Announce Type: new Abstract: Deep vision models exploit shortcuts, relying on cues that correlate with supervision signals. Prior work has focused on visible biases, such as object-
arXiv:2603.26154v2 Announce Type: replace Abstract: Image-to-video (I2V) generation models can be misused to animate a single image into a convincing fake video, motivating perturbation-based image pr
Since now we have kimi k3 and next week we are getting Qwen 3.8 Max and also soon V4 pro Deepseek. I am curious if the old power house like Kimi 2.6/7 code and GLM.5.2 are all that relevant. especiall
arXiv:2608.06122v1 Announce Type: cross Abstract: Inspired by recent evidence that transformer architectures benefit from Self-PreTraining (SPT) on long-context benchmarks, we investigate whether simi
arXiv:2608.06014v1 Announce Type: new Abstract: Should a completion model spend extra test-time compute by iterating, or spend a similar parameter budget on a wider one-shot predictor? The answer is e
arXiv:2608.05718v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) photogrammetry requires camera networks that provide sufficient surface coverage, image overlap, parallax, and resolution,
arXiv:2608.05674v1 Announce Type: new Abstract: Robot data is scarce, so generalist policies need to learn from heterogeneous sources, including human egocentric video, simulation, and real robots, wh
arXiv:2608.05594v1 Announce Type: cross Abstract: Validation adequacy in safety-critical software depends on more than the system under test. Critical scenarios must be constructed under controlled co
Just saw that the LLMs-from-scratch repository passed 100,000 stars on GitHub! This is super cool and motivating. I am really happy to see that this open-source repo has helped so many people. Thanks
arXiv:2608.06107v1 Announce Type: new Abstract: Machine learning offers a promising avenue to accelerate physical simulations by replacing computationally expensive traditional Partial Differential Eq
arXiv:2608.05647v1 Announce Type: new Abstract: This article presents a kinematic-inertial-LiDAR-visual odometry for humanoid robots, called KILVO. Tailored to the platform features, requirements, and
arXiv:2608.05475v1 Announce Type: new Abstract: Task knowledge is commonly stored either as text in the prompt or as an update to model weights. Text is modular but must be interpreted on every use, w
arXiv:2608.05798v1 Announce Type: new Abstract: Latent diffusion modeling (LDM), a prominent paradigm, utilizes tokenizers to map input signal to compressed representation. This dependency positions t
LabyrinthBench measures the thing that actually kills long agent runs — whether a model can still use what it learned twenty turns ago — deterministically, with no LLM judge, on your own hardware, wit
arXiv:2608.06041v1 Announce Type: cross Abstract: Large language models (LLMs) have been shown to exhibit strong Python preferences when generating project-level code, but there is currently no system
arXiv:2608.05157v1 Announce Type: cross Abstract: Double blind peer review serves as the scientific community primary defense against status and affiliation bias. Its effectiveness rests on the assump
arXiv:2307.12022v3 Announce Type: replace-cross Abstract: Optimizing individualized treatment sequences for patients who weigh multiple, competing outcomes differently poses a challenge for dynamic tr
arXiv:2608.05706v1 Announce Type: new Abstract: World models enable agents to perform forward rollout and planning without real-world interaction. However, their application in open-world embodied int
arXiv:2601.04098v2 Announce Type: replace-cross Abstract: Transformer language models systematically prefer tokens at specific input positions regardless of semantic relevance---a phenomenon known as
arXiv:2608.05600v1 Announce Type: cross Abstract: Flow-based generative models are typically sampled by solving a deterministic ordinary differential equation (ODE), whereas online reinforcement learn
arXiv:2608.05610v1 Announce Type: cross Abstract: QAOA training repeatedly queries an objective and all shared gradients, making exact evaluation a feasibility bottleneck even when QUBO terms have bou
arXiv:2608.05493v1 Announce Type: cross Abstract: Language models (LMs) are increasingly used to interact with external services via programs written in domain-specific languages (DSLs). Unfortunately
arXiv:2608.06060v1 Announce Type: new Abstract: Unified multimodal retrieval aims to identify candidates that satisfy complex user intent expressed through heterogeneous inputs. Although Large Vision-
arXiv:2608.06153v1 Announce Type: cross Abstract: Automated skill evolution enables Large Language Model (LLM) agents to continuously improve without expensive retraining. However, existing approaches
arXiv:2608.05819v1 Announce Type: new Abstract: Classical simulation remains essential for developing and validating quantum algorithms, but its cost grows rapidly with circuit size. Tensor-network co
arXiv:2608.06142v1 Announce Type: new Abstract: Composition, the deliberate arrangement of visual elements, is central to how meaning, emotion, and aesthetic quality are conveyed in artwork, yet it re
arXiv:2608.06377v1 Announce Type: cross Abstract: Language models increasingly condition their answers on external signals, and a single misleading one can turn a correct answer wrong. The obvious rem
Harvey AI Corp., a provider of artificial intelligence software for attorneys, is reportedly seeking at least 500 million in new funding. The Information today cited sources as saying that the round c
arXiv:2601.05192v2 Announce Type: replace Abstract: Entity linking (mapping ambiguous mentions in text to entities in a knowledge base) is a foundational step in tasks such as knowledge graph construc
LFM2.5-2.6B is a new tiny model by LiquidAI, with benchmarks that put it head to head with much larger models. I've run llama-perplexity on many model GGUF quants, crossed with many KV cache quants, t
arXiv:2608.05727v1 Announce Type: cross Abstract: Neural Audio Codecs are widely adopted in speech generation and editing. However, existing neural audio codecs are not idempotent: across the paper's
arXiv:2608.05739v1 Announce Type: new Abstract: Mobile image denoising requires both good restoration quality and low computational cost. In addition, it's annoying to collect large-scale LQ-GT clean
Live now: our Local AI Track from AI Engineer World's Fair 2026, brought to you by @nvidia. Thesis: frontier intelligence is becoming something you own. https://www.youtube.com/watch?v=KB41dTlX1Uc&lis
A fresh llama.cpp PR (#26689) changes what looks like a tiny SYCL FlashAttention dispatch decision. With a quantized KV cache ('q4_0' / 'q8_0'), decode was being sent through the VEC kernel. On the au
arXiv:2608.06135v1 Announce Type: new Abstract: Large Language Models (LLMs) such as ChatGPT and Claude are widely used for information retrieval and problem-solving. Recent work has focused on improv
arXiv:2608.05356v1 Announce Type: new Abstract: High-definition 3D LiDAR maps are important for autonomous driving and smart-city services, which require reliable detection of object-level changes in
arXiv:2604.01280v2 Announce Type: replace-cross Abstract: Knowledge-based Visual Question Answering (KB-VQA) requires Multimodal Large Language Models (MLLMs) to identify and combine fine-grained visu
arXiv:2608.05246v1 Announce Type: new Abstract: Existing personalized LLM benchmarks primarily rely on textual personas or isolated behavioral signals, providing limited evaluation of cross-domain beh
arXiv:2608.05817v1 Announce Type: new Abstract: Metaphor enables the understanding of abstract concepts through cross-domain mappings while conveying affective attitudes. In multimodal scenarios, visu
arXiv:2607.16284v2 Announce Type: replace Abstract: Micro-Actions (MAs) are subtle and spontaneous human behaviors that provide important non-verbal cues in social interaction and affective communicat
arXiv:2608.05872v1 Announce Type: cross Abstract: Standard Large Language Models (LLMs) execute layers sequentially. Dynamic layer routing, i.e. search for a different execution path through layers in
arXiv:2608.05850v1 Announce Type: cross Abstract: We present MameLoshnLM, the first open-source 8B-parameter language model built specifically for Yiddish. Despite Yiddish's rich textual tradition, it
**Managing AI Coding Costs at Scale** This article addresses the economic challenges of deploying AI coding tools across large teams or organizations. It explores strategies for tracking resource usag
arXiv:2608.05911v1 Announce Type: new Abstract: This paper presents an end-to-end, IIIF-based pipeline that turns the digitised Armenian press of France into an interactive map of the 20th-century Par
arXiv:2510.03997v2 Announce Type: replace Abstract: Understanding how patients perceive their physicians is essential to improving trust, communication, and satisfaction. Patients increasingly consult
arXiv:2608.05857v1 Announce Type: new Abstract: Retrieval-Augmented Generation systems rely on similarity scores to retrieve relevant content, yet scores are not directly comparable across embedding m
arXiv:2608.05209v1 Announce Type: new Abstract: Constructing reliable online HD maps remains challenging in dynamic urban environments due to moving objects and occlusions. While recent works employ f
arXiv:2608.05243v1 Announce Type: cross Abstract: Factorized generative models commonly regularize a latent style variable z_s by matching its marginal distribution to a fixed Gaussian prior and inter
arXiv:2608.06257v1 Announce Type: new Abstract: Current video world models struggle in multiplayer environments because they entangle world state with view-dependent visual latents, leading to redunda
arXiv:2606.21140v2 Announce Type: replace-cross Abstract: Rapid advances in large language models have improved the task-solving capabilities of command-line-interface (CLI)-based agents, whose CLIs d
arXiv:2608.05472v1 Announce Type: cross Abstract: Multi-head attention combines an input-dependent softmax routing with an input-independent linear value projection, so the per-sample operator mapping
arXiv:2608.05878v1 Announce Type: new Abstract: Text-to-image diffusion transformers learn about objects and scenes by learning to generate them, making them strong candidates for training-free zero-s
arXiv:2608.05152v1 Announce Type: cross Abstract: Large language models (LLMs) with chain-of-thought reasoning have been widely applied in recent years, and theoretical explanations of their behavior
arXiv:2608.05624v1 Announce Type: new Abstract: Sycophantic responses are becoming pervasive in large language models (LLMs), and prior work has pointed out that some of them could be harmful. This pa
As AI agents gain access to enterprise systems and sensitive data, security teams need greater visibility into their actions. Real-time monitoring and policy enforcement are becoming essential as a pa
arXiv:2608.06253v1 Announce Type: new Abstract: Metabolomics knowledge is distributed across heterogeneous resources and remains difficult to translate into predictive representations. We developed Me
arXiv:2608.06183v1 Announce Type: new Abstract: Microarchitecture design space exploration suffers from expansive search spaces and expensive PPA evaluation, leaving only a small simulation budget for