Knowledge catalogue
arXiv:2608.04057v1 Announce Type: cross Abstract: Top-k selection determines which components of a sparse model remain active. Hard selection blocks gradients, while continuous relaxations often coupl
arXiv:2608.04186v1 Announce Type: new Abstract: This paper presents a conceptual framework for developing an electronic explanatory dictionary of the Tajik language using large language models (LLMs).
arXiv:2503.10367v2 Announce Type: replace-cross Abstract: Edge devices host domain-specific small language models (SLMs) with limited resources, while private clouds offer larger LLMs. We propose G-Bo
arXiv:2608.04519v1 Announce Type: new Abstract: Benchmarking machine unlearning methods is critical to understand whether sensitive knowledge is removed from large language models (LLMs) or not. Curre
arXiv:2608.04545v1 Announce Type: new Abstract: We study the problem of learning compact rule-based compressors for structured network traffic. Each packet is a record of header fields that are highly
arXiv:2509.12154v2 Announce Type: replace Abstract: The first part of this paper studies the evolution of gradient flow for homogeneous neural networks near a class of saddle points exhibiting a spars
arXiv:2608.04056v1 Announce Type: new Abstract: When people label text for sexism, they often disagree, and not because some of them are wrong: they genuinely perceive sexism differently. Most NLP sys
arXiv:2608.04027v1 Announce Type: new Abstract: This work investigates the feasibility of augmenting traditional R-Matrix codes with a robust machine learning framework for automatically detecting neu
arXiv:2608.05084v1 Announce Type: new Abstract: Diffusion policies are a powerful policy class for continuous control, but their iterative denoising process creates a substantial computational bottlen
arXiv:2608.05100v1 Announce Type: new Abstract: Self-supervised pretraining objectives are spatially uniform: the teacher temperature and the per-patch loss weight are identical everywhere in the imag
arXiv:2607.09290v2 Announce Type: replace-cross Abstract: In the digital era, Portable Document Format (PDF) is one of the most widely used file formats for storing and exchanging digital documents du
arXiv:2305.06177v1 Announce Type: cross Abstract: We present a thermodynamic analysis of a quantum engine that uses a single quantum particle as its working fluid, inspired by Szilard's classical sing
arXiv:2608.04147v1 Announce Type: cross Abstract: Label noise is common in medical imaging datasets due to factors such as inter-rater variability, annotation errors, and ambiguous cases. This can sev
arXiv:2608.04028v1 Announce Type: cross Abstract: Echo-state networks enable efficient temporal learning by fixing the recurrent dynamics and training only a linear readout. However, conventional rese
arXiv:2608.05016v1 Announce Type: cross Abstract: Predicting the existence and type of links (edges) between nodes in a multi-relational graph is key for applications from social interaction predictio
arXiv:2410.10783v4 Announce Type: replace Abstract: The large-scale training of multi-modal models on data scraped from the web has shown outstanding utility in infusing these models with the required
arXiv:2608.04271v1 Announce Type: cross Abstract: Just like software and hardware, business processes are susceptible to vulnerabilities that can lead to product quality issues, delays, and increased
The Amazon SageMaker Python SDK v3 now exposes generative AI inference recommendations in Amazon SageMaker AI directly in your notebook. Benchmark an endpoint, generate data-driven deployment recommen
arXiv:2606.18709v2 Announce Type: replace Abstract: Existing work on LLM-based educational assessment has focused largely on item difficulty, but difficulty alone does not indicate whether an item mea
arXiv:2608.04474v1 Announce Type: new Abstract: Data-driven decision pipelines combining predictive machine learning models with downstream optimization software are increasingly used to make high-sta
The quality of open-weight language models has dramatically improved in recent years. Sharing weights greatly facilitates model adoption by enabling their use across diverse hardware and software plat
arXiv:2608.02491v2 Announce Type: replace Abstract: Language models have taken on the role of a very new type of technology, by virtue of their 'human-ness' and rapid integration into users' daily liv
arXiv:2608.04347v1 Announce Type: new Abstract: Fine-tuning enables a source model to acquire desired capabilities and behaviors in a target domain while retaining much of its general-purpose competen
arXiv:2608.04106v1 Announce Type: new Abstract: Dense image matching establishes pixel-wise correspondences and underpins broad applications in computer vision and photogrammetry. However, extending d
Luna non-reasoning is a bit better than GPT 4o which was sota 2 years ago. Luna (medium) thinking is a bit better than GPT-5 (High) which was sota 1 year ago. Now free to everyone unlimited Sol Max/Fa
arXiv:2608.05088v1 Announce Type: new Abstract: Muon has recently emerged as a promising alternative to AdamW for language model pretraining by orthogonalizing momentum matrices using Newton-Schulz it
arXiv:2608.02347v2 Announce Type: replace Abstract: Recurrent linear attention models (RLAs) such as Mamba offer efficient linear-time sequence modeling as an alternative to Transformers, yet their fi
arXiv:2608.04365v1 Announce Type: new Abstract: Audits have emerged as a critical instrument for algorithmic governance, providing a mechanism for external scrutiny and governance of machine learning
arXiv:2608.05054v1 Announce Type: cross Abstract: We investigate the transferability of Earth weather foundation models to planetary atmospheres by adapting the GraphCast graph neural weather forecast
arXiv:2608.04624v1 Announce Type: cross Abstract: Current neural networks for beat tracking generate invalid outputs, such as consecutive downbeats and erratic tempo changes, even when these are not p
arXiv:2502.19058v2 Announce Type: replace Abstract: Synthetic mathematical data has become an important resource for scaling the reasoning capabilities of large language models, yet errors in generate
arXiv:2608.04205v1 Announce Type: new Abstract: Human evaluation of AI systems and digital products is costly, slow, and difficult to scale. Offline evaluations are more scalable but often abstract aw
arXiv:2510.21084v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown strong potential for clinical decision support through their advanced language understanding and reaso
arXiv:2602.07885v2 Announce Type: replace Abstract: Long-term memory enables large language model agents to tackle complex tasks through historical interactions. However, existing frameworks encounter
arXiv:2509.08604v5 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated significant potential in medicine, with many studies adapting them through continued pre-traini
arXiv:2608.04433v1 Announce Type: cross Abstract: We present MERaLiON-GR, a speech gender recognition system that performs binary classification (female / male) on English and Southeast Asian (SEA) la
arXiv:2608.04407v1 Announce Type: cross Abstract: Memory-efficient matrix optimizers such as Sinkhorn gradient descent remove most AdamW optimizer state for dense Transformer matrices, but direct appl
Meta Platforms Inc. is getting more serious in its efforts to challenge leading artificial intelligence labs Anthropic PBC and OpenAI PBC with the release of its first AI coding agent, called Muse Cod
A large language model developed by Meta Platforms Inc. hacked a third party organization during a cybersecurity evaluation. The Facebook parent disclosed the incident on Wednesday without specifying
arXiv:2608.04587v1 Announce Type: new Abstract: Long-form video understanding requires locating sparse, question-relevant evidence in long, multimodal videos. Real-world video distributions differ in
arXiv:2608.04805v1 Announce Type: new Abstract: Leak detection models for multiphase pipelines often degrade when deployed under flow regimes that differ from training. Existing evaluations typically
arXiv:2608.04307v1 Announce Type: cross Abstract: Text summarization is deceptively difficult. While condensing information seems straightforward, real-world enterprise summarization of support ticket
Salve a tutti. Sto valutando di mettere dei modelli locali, magari su LM studio o altro software se mi spiegate il perché da utilizzare sia come PT sia per Soc L2/L3. Ho un PC con 128 GB RAM ddr5 8gb
arXiv:2608.04933v1 Announce Type: new Abstract: Long-horizon embodied task requires agents to act under partial observability while preserving both scene belief and execution progress. Flat histories
arXiv:2608.04160v1 Announce Type: new Abstract: Multilingual evaluations report accuracy at a single output-token cap, but languages need different numbers of tokens to express the same content, so th
arXiv:2608.04633v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) methods improve generalization by aligning their representations with 3D scene geometry. However, these methods are
arXiv:2608.04157v1 Announce Type: new Abstract: Recurrence plots are a time series data mining primitive applied to a variety of domains (e.g. star light curves, sound waveforms, CCT telemetry). This
Nearly every major AI lab uses Google Cloud infrastructure, including for training of models, inference for agents, and new frontier research. Google Cloud also continues to be the platform of choice
arXiv:2607.18559v2 Announce Type: replace-cross Abstract: Gaussian graphical model selection is usually studied under independent sampling, but in many applications the data arise as a single trajecto
arXiv:2603.00828v2 Announce Type: replace Abstract: In recent years, various methods have been proposed for mesh analysis, each offering distinct advantages and often excelling on different object cla
arXiv:2608.04680v1 Announce Type: cross Abstract: To adopt the Vision Transformers (ViTs) in resource-constrained environment, token pruning is widely used to reduce computational cost without impacti
arXiv:2608.04657v1 Announce Type: new Abstract: World action models (WAMs) built on video generation backbones are a rising recipe for robot learning, yet remain confined to tabletop manipulation. Mob
arXiv:2506.02260v4 Announce Type: replace-cross Abstract: Wearable devices enable continuous multi-modal physiological and behavioral monitoring, yet analysis of these data streams faces fundamental c
arXiv:2608.04054v1 Announce Type: cross Abstract: Multimodal intent recognition requires understanding not only what textual, acoustic, and visual signals share, but also how they disagree. Such disag
arXiv:2608.04023v1 Announce Type: cross Abstract: Sri Lanka's fisheries sector is important for jobs and food supply. Between 2019 and 2025, it faced several major problems at the same time, and how t
arXiv:2608.04071v1 Announce Type: new Abstract: Automatically generating professional multimodal reports comprising both textual analysis and visual charts from structured tabular data is a critical c
arXiv:2604.00513v3 Announce Type: replace-cross Abstract: With the rapid growth of e-commerce, exploring general representations rather than task-specific ones has attracted increasing attention. Alth
arXiv:2608.04455v1 Announce Type: cross Abstract: One of the most challenging problems entertainment live-streaming services face in recommendation systems is that user behaviors are sparse and delaye
arXiv:2608.04722v1 Announce Type: new Abstract: Creating photorealistic 3D human avatars with realistic upper-body motion remains challenging. Existing approaches either focus on the head and overlook
arXiv:2511.11413v2 Announce Type: replace Abstract: Consider the problem of finding the best matching in a weighted graph where we only have access to predictions of the actual stochastic weights, bas