Knowledge catalogue
arXiv:2604.18893v1 Announce Type: cross Abstract: A series of high-profile tragedies involving companion chatbots has triggered an unusually rapid regulatory response. Several jurisdictions, including
arXiv:2604.19720v1 Announce Type: new Abstract: Human video generation remains challenging due to the difficulty of jointly modeling human appearance, motion, and camera viewpoint under limited multi-
arXiv:2604.19104v1 Announce Type: cross Abstract: Developing bipedal football robots in dynamiccombat environments presents challenges related to motionstability and deep coupling of multiple tasks, a
arXiv:2604.19060v1 Announce Type: new Abstract: Accurate disease classification from radiology reports is essential for many applications. While supervised fine-tuning (SFT) of lightweight LLMs improv
arXiv:2604.19099v1 Announce Type: cross Abstract: Education is not merely the transmission of information or the optimisation of individual performance; it is a fundamentally social, constructive, and
arXiv:2604.18738v1 Announce Type: new Abstract: Masked diffusion language models such as LLaDA2.1 rely on Token-to-Token (T2T) editing to correct their own generation errors: whenever a different toke
arXiv:2505.06335v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has the potential for simultaneous global learning amongst a large number of parallel agents, enabling emerging AI suc
arXiv:2509.13281v5 Announce Type: replace Abstract: Current safety evaluations of language models rely on benchmark-based assessments that may miss localized vulnerabilities. We present RepIt, a simpl
arXiv:2503.16251v2 Announce Type: replace-cross Abstract: Federated Learning (FL) has gained prominence in machine learning applications across critical domains by enabling collaborative model trainin
arXiv:2603.26815v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) systems for financial document question answering typically follow a chunk-based paradigm: documents are
arXiv:2410.03294v4 Announce Type: replace Abstract: This study addresses the deployment challenges of integer-only quantized Transformers on resource-constrained embedded FPGAs (Xilinx Spartan-7 XC7S1
arXiv:2604.18811v1 Announce Type: cross Abstract: Despite the perceived success of large-scale dataset distillation (DD) methods, recent evidence finds that simple random image baselines perform on-pa
arXiv:2505.20816v2 Announce Type: replace Abstract: Recent advances in multimodal question answering have primarily focused on combining heterogeneous modalities or fine-tuning multimodal large langua
arXiv:2604.19299v1 Announce Type: cross Abstract: Despite the impressive capabilities of large language models, their substantial computational costs, latency, and privacy risks hinder their widesprea
arXiv:2604.19523v1 Announce Type: new Abstract: Social deduction games such as Mafia present a unique AI challenge: players must reason under uncertainty, interpret incomplete and intentionally mislea
arXiv:2604.18757v1 Announce Type: cross Abstract: The retina provides a unique, noninvasive window into Alzheimer's disease (AD) and dementia, capturing early structural changes through morphometric f
arXiv:2604.19401v1 Announce Type: cross Abstract: Knowledge Graph Embeddings (KGEs) support a wide range of downstream tasks over Knowledge Graphs (KGs). In practice, KGs evolve as new entities and fa
arXiv:2604.19528v1 Announce Type: cross Abstract: This technical note revisits the relationship between RaBitQ and TurboQuant under a unified comparison framework. We compare the two methods in terms
arXiv:2604.19570v1 Announce Type: new Abstract: Accurate medical image segmentation requires both long-range contextual reasoning and precise boundary delineation, a task where existing transformer- a
arXiv:2604.01375v2 Announce Type: replace Abstract: Rubric-based evaluation is widely used in LLM benchmarks and training pipelines for open-ended, less verifiable tasks. While prior work has demonstr
arXiv:2602.11675v3 Announce Type: replace Abstract: Large language models may answer causal questions correctly for the wrong reasons, substituting associational shortcuts P(Y|X) for the interventiona
Rivian and Volkswagen Group's joint venture put Devin to work on testing and ticket triage across a software platform that will power up to 30M vehicles. Devin handles autonomous ticket triage in Slac
arXiv:2604.19146v1 Announce Type: new Abstract: Particle accelerator beamline optimization is a high-dimensional control problem traditionally requiring significant expert intervention. We present RLA
arXiv:2604.19092v1 Announce Type: cross Abstract: Recent advances in large-scale video world models have enabled increasingly realistic future prediction, raising the prospect of leveraging imagined v
arXiv:2604.19108v1 Announce Type: cross Abstract: As a means to balance the growth of the AI industry with the need for privacy protection, machine unlearning plays a crucial role in realizing the ``r
arXiv:2604.19593v1 Announce Type: cross Abstract: The importance of clear and correct text in legal documents cannot be understated, and, consequently, a grammatical error correction tool meant to ass
arXiv:2604.19025v1 Announce Type: new Abstract: Widespread RGB-Depth (RGB-D) sensors and advanced 3D reconstruction technologies facilitate the capture of indoor spaces, improving the fields of augmen
Fireworks AI announced the appointment of George Hu as President of the company. The announcement came from Fireworks AI's leadership, noting that Hu and the company's founder met approximately a year
Cloud data management and data security company Rubrik Inc. today announced a deepening of its partnership with Google Cloud with two new integrations that extend its reach into managed database prote
arXiv:2604.19072v1 Announce Type: cross Abstract: Semi-supervised learning with manifold regularization is a classical framework for jointly learning from both labeled and unlabeled data, where the ke
This post discusses concerns about AI model degradation through the inclusion of low-quality or irrelevant training data, using butternut squash image generation as a humorous example of how excessive
arXiv:2604.19737v1 Announce Type: new Abstract: Reinforcement learning (RL) offers a compelling data-driven paradigm for synthesizing controllers for complex systems when accurate physical models are
arXiv:2604.19639v1 Announce Type: cross Abstract: Modern world models are becoming too complex to admit explicit dynamical descriptions. We study safety-critical contextual control, where a Planner mu
arXiv:2604.19638v1 Announce Type: new Abstract: Multimodal Large Language Models are increasingly adopted as autonomous agents in interactive environments, yet their ability to proactively address saf
arXiv:2601.04237v2 Announce Type: replace Abstract: We demonstrate SAGE-32B, a 32 billion parameter language model that focuses on agentic reasoning and long range planning tasks. Unlike chat models t
arXiv:2604.19623v1 Announce Type: cross Abstract: Edge-cloud hybrid inference offloads difficult inputs to a powerful remote model, but the uplink channel imposes hard per-request constraints on the n
arXiv:2604.19098v1 Announce Type: cross Abstract: English financial NLP has progressed rapidly through benchmarks for sentiment, document understanding, and financial question answering, while Arabic
arXiv:2604.19048v1 Announce Type: cross Abstract: The combination of Mixture-of-Experts (MoE) and Low-Rank Adaptation (LoRA) has shown significant potential for enhancing the multi-task learning capab
arXiv:2604.18982v1 Announce Type: new Abstract: Social intelligence, the ability to navigate complex interpersonal interactions, presents a fundamental challenge for language agents. Training such age
arXiv:2604.19157v1 Announce Type: new Abstract: KV-cache memory is a major bottleneck in real-world LLM serving, where systems must simultaneously support latency-sensitive small-batch requests and hi
arXiv:2604.19343v1 Announce Type: cross Abstract: Memristive devices present a promising foundation for next-generation information processing by combining memory and computation within a single physi
arXiv:2604.19275v1 Announce Type: cross Abstract: Modern UAV architectures increasingly aim to unify high-level autonomy and low-level flight control on a single General-Purpose Operating System (GPOS
I can't provide a summary of this content because the post text is incomplete (ends with 'well, you c…'), making it impossible to accurately describe what prediction was made or what Adams allegedly s
arXiv:2604.18722v1 Announce Type: new Abstract: Cross-lingual transfer in NLP is often hindered by the ``script barrier'' where differences in writing systems inhibit transfer learning between languag
arXiv:2604.19185v1 Announce Type: cross Abstract: Small language models (SLMs), such as BART, can achieve summarization performance comparable to large language models (LLMs) via distillation. However
Politico: Sean Plankey, President Trump's pick to lead CISA, withdraws from consideration after resistance from Sen. Rick Scott stalled his nomination for over a year — Spokespeople for the White Hous
arXiv:2506.14387v3 Announce Type: replace Abstract: Adapting LLMs with new knowledge is increasingly important, but standard fine-tuning often erodes aligned epistemic abstention: the ability to ackno
arXiv:2602.02063v2 Announce Type: replace-cross Abstract: Automated vehicles lack natural communication channels with other road users, making external Human-Machine Interfaces (eHMIs) essential for c
arXiv:2604.19489v1 Announce Type: new Abstract: This paper presents a computational case study that evaluates the capabilities of specialized machine learning models and emerging multimodal large lang
arXiv:2604.18966v1 Announce Type: cross Abstract: While language models have been adapted for tabular data generation, two fundamental limitations remain: (1) static fine-tuning produces models that c
arXiv:2603.27134v3 Announce Type: replace Abstract: Are there still barriers to generalization once all relevant variables are known? We address this question via a framework that casts compositional
arXiv:2604.18835v1 Announce Type: cross Abstract: We propose a scalable, multifactorial experimental framework that systematically probes LLM sensitivity to subtle semantic changes in pairwise documen
arXiv:2601.18027v2 Announce Type: replace Abstract: LLM agents are increasingly used for social simulation, yet emotion is often treated as a transient cue, causing emotional amnesia and weak long-hor
arXiv:2604.19560v1 Announce Type: new Abstract: The goal of machine learning is to find models that minimize prediction error on data that has not yet been seen. Its operational paradigm assumes acces
Lola Murti / CNBC: ServiceNow reports Q1 subscription revenue up 22% YoY to 3.67B, vs. 3.65B est., says conflict in the Middle East weighed on growth; NOW drops 12%+ after hours — ServiceNow reported
ServiceNow Inc. today delivered first-quarter results that surpassed Wall Street’s expectations, but its stock fell hard in late trading after it said the ongoing war in Iran was dragging on its subsc
arXiv:2604.19254v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning (PEFT) reduces the training cost of full-parameter fine-tuning for large language models (LLMs) by training only a sma
arXiv:2604.19219v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training among multiple parties without centralizing raw data. There are two main paradigms in FL:
🆕 Shopify's AI-Native Engineering: 100% adoption, unlimited tokens, Tangle, Tangent, & SimGym https://www.latent.space/p/shopify @Shopify CTO @MParakhin explains why near-universal AI adoption is chan
Shopify's CTO Mikhail Parakhin discusses the company's transition into an AI-centric phase, highlighting anticipated AI usage explosion in 2026, the adoption of unlimited Claude Opus-4.6 token budgets