Knowledge catalogue
Emad Mostaque expressed anticipation for the integration of Google's Gemini Omni multimodal AI model into NotebookLM's cinematic explainer video generation features. The post suggests potential upcomi
arXiv:2603.22570v2 Announce Type: replace Abstract: Active computer vision promises efficient, biologically plausible perception through sequential, localized glimpses, but lacks scalable general-purp
arXiv:2605.17110v1 Announce Type: new Abstract: Query clustering organizes queries into groups that reflect shared latent capability demands, enabling capability-aware LLM evaluation. Existing cluster
arXiv:2605.16901v1 Announce Type: new Abstract: Segment Anything Models (SAMs) are extensively used in computer vision for universal image segmentation, but deploying them on resource-constrained devi
arXiv:2508.06524v2 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly follow neural scaling laws that tie performance gains to rapidly expanding computational budgets, ra
arXiv:2605.17176v1 Announce Type: new Abstract: Emotion understanding is a core capability for LLMs to interact effectively with humans, yet existing evaluation paradigms rely on discrete emotion labe
arXiv:2605.16919v1 Announce Type: cross Abstract: Many decision-facing stochastic systems are observed through aggregate distributions rather than scalar trajectories: queue occupancies, mobility shar
arXiv:2605.17528v1 Announce Type: cross Abstract: Large Language Models (LLMs) generate realistic synthetic data but offer no guarantee that their outputs respect the causal mechanisms governing the t
arXiv:2605.18610v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown remarkable ability in aligning visual and textual representations, enabling a wide range of multimodal applic
arXiv:2605.17254v1 Announce Type: new Abstract: Property prediction and inverse structural design of catalytic materials are typically modeled as two independent tasks: the former predicts target prop
arXiv:2505.02360v2 Announce Type: replace-cross Abstract: Adversarial training is a cornerstone of robust deep learning, but fast methods like the Fast Gradient Sign Method (FGSM) often suffer from Ca
arXiv:2605.18054v1 Announce Type: cross Abstract: Volumetric media promises next-generation content delivery applications, but its bandwidth demand remains a key bottleneck. Implicit and hybrid volume
arXiv:2605.17334v1 Announce Type: cross Abstract: Reliable early detection of lithium-ion battery degradation requires health indicators that are physically interpretable and computable from routine c
arXiv:2603.13652v2 Announce Type: replace Abstract: Attribution methods for Vision Transformers (ViTs) aim to identify image regions that influence model predictions, but producing faithful and well-l
arXiv:2307.09575v2 Announce Type: replace-cross Abstract: This paper investigates causal influences between agents linked by a social graph and interacting over time. In particular, the work examines
arXiv:2605.17641v1 Announce Type: new Abstract: Long-horizon LLM agents rely on persistent memory to support interactions across sessions, yet existing memory systems often retrieve context using sema
arXiv:2605.18327v1 Announce Type: new Abstract: AI agents deployed into SRE workflows currently derive their understanding of environment state from raw observability telemetry at query time, paying a
arXiv:2605.16416v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved strong performance on general multimodal reasoning, yet remain challenged in integrating nonlocal visual i
arXiv:2502.18663v3 Announce Type: replace Abstract: This paper is the second in a series of studies on developing efficient artificial intelligence-based approaches to pathfinding on extremely large g
arXiv:2605.17370v1 Announce Type: new Abstract: Cognitive behavioural therapy is widely used to help patients understand and manage psychological distress. It is often delivered through spoken convers
Cerebras is now running Kimi K2.6 – a trillion parameter model – in enterprise trials. At ~1,000 tokens/s, this is the fastest frontier model performance ever measured by Artificial Analysis @Artifici
Bloomberg: CertiK: physical attacks on crypto holders rose 75% YoY to 72 confirmed cases and 41M in known losses in 2025; Coinbase spent ~7.6M to protect Brian Armstrong — After a year of kidnappings,
arXiv:2605.17164v1 Announce Type: cross Abstract: Deploying large-scale LLM training and inference with optimal performance is exceptionally challenging due to a complex design space of parallelism st
arXiv:2605.16274v1 Announce Type: cross Abstract: Charts are the dominant medium for visualizing data, discovering patterns and trends, and communicating data driven insights, yet designing them still
arXiv:2605.16377v1 Announce Type: cross Abstract: Transparent and standardized reporting is essential for reproducible scientific research, yet adherence to reporting guidelines remains inconsistent b
arXiv:2605.17214v1 Announce Type: new Abstract: While Large Language Models (LLMs) have revolutionized scientific text processing, they exhibit a significant capability gap when interpreting chemical
arXiv:2605.16679v1 Announce Type: cross Abstract: End-to-end automation of realistic healthcare operations stresses three capabilities underrepresented in current benchmarks: policy density, decisions
Bloomberg: Chinese flash memory chipmaker YMTC says it officially initiated a pre-listing tutoring process with local brokers, marking the first formal step toward an IPO — Yangtze Memory Technologies
arXiv:2605.16388v1 Announce Type: new Abstract: Semantic communication (SC) aims to reduce transmission overhead by conveying task-relevant information rather than raw data. However, existing SC appro
arXiv:2605.18328v1 Announce Type: new Abstract: LED Virtual Production (VP) uses large LED volumes to render backgrounds in real time, enabling in-camera visual effects but making post-shot changes la
arXiv:2605.17458v1 Announce Type: new Abstract: Text classification models are typically trained via supervised fine-tuning (SFT). However, SFT essentially performs behavior cloning from instance-wise
arXiv:2605.17284v1 Announce Type: cross Abstract: End-to-end autonomous driving systems powered by Vision-Language-Action (VLA) models achieve strong performance on common driving scenarios, yet remai
arXiv:2604.04202v2 Announce Type: replace-cross Abstract: AI agents deployed as persistent assistants must maintain correct beliefs as their information environment evolves. In practice, evidence is s
arXiv:2602.05126v2 Announce Type: replace Abstract: Human papillomavirus (HPV) status is a critical determinant of prognosis and treatment response in head and neck and cervical cancers. Although atte
arXiv:2512.23178v3 Announce Type: replace-cross Abstract: Optimization under heavy-tailed noise has become popular recently, since it better fits many modern machine learning tasks, as captured by emp
arXiv:2605.16984v1 Announce Type: new Abstract: We present our submission to the LLM track of the 2026 Computational Models of Reference, Anaphora and Coreference (CRAC 2026) shared task. With an aver
arXiv:2605.18680v1 Announce Type: new Abstract: Metaverse platforms rely on creator-driven marketplaces where avatars are assembled from discrete, taxonomy-labeled 3D assets (e.g., tops, bottoms, shoe
arXiv:2605.16832v1 Announce Type: new Abstract: Large language models (LLMs) have recently been used as structured decoders for indoor understanding from 3D point-token inputs. However, point cloud en
arXiv:2605.18747v1 Announce Type: cross Abstract: Recent large language models (LLMs) have demonstrated strong capabilities in understanding and generating code, from competitive programming to reposi
arXiv:2605.18451v1 Announce Type: new Abstract: Designing realistic and functional 3D indoor rooms is essential for a wide range of applications, including interior design, virtual reality, gaming, an
arXiv:2605.18257v1 Announce Type: cross Abstract: Multimodal representation alignment is pivotal for large language models and robotics. Traditional methods are often hindered by cross-modal informati
arXiv:2602.17684v2 Announce Type: replace-cross Abstract: Reinforcement Learning from Verifiable Rewards (RLVR) has driven recent progress in code large language models by leveraging execution-based f
arXiv:2603.09286v2 Announce Type: replace Abstract: Beyond conveying semantic information, images also possess cognitive properties that elicit specific psychological responses from viewers, such as m
arXiv:2605.17135v1 Announce Type: new Abstract: Annotating large-scale LiDAR point clouds for 3D semantic segmentation is costly and time-consuming, which motivates the use of semi-supervised learning
arXiv:2605.18288v1 Announce Type: new Abstract: Unsupervised fine-grained image hashing aims to learn compact binary codes that preserve subtle visual differences among highly similar instances withou
arXiv:2509.26037v2 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) with Neural Architecture Search (NAS) has introduced new possibilities for automating the design of
arXiv:2507.22136v3 Announce Type: replace Abstract: Humans possess innate meta-learning capabilities, partly attributable to their exceptional color perception. In this paper, we pioneer an innovative
The baby chicks were shifting and starting to pip—or trying to hatch. But not from an egg. Instead, these chickens were growing inside transparent 3D-printed plastic cups at the Dallas headquarters of
arXiv:2503.13934v2 Announce Type: replace-cross Abstract: Mobile robot navigation in dynamic environments with pedestrian traffic is a key challenge in the development of autonomous mobile service rob
arXiv:2605.18284v1 Announce Type: cross Abstract: Software repositories accumulate large amounts of unstructured knowledge in commit messages, pull-request discussions, and issue threads, but develope
arXiv:2605.16839v1 Announce Type: new Abstract: Chunked prefill has become a widely adopted serving strategy for long-context large language models, but efficient attention computation in this regime
arXiv:2504.16397v2 Announce Type: replace-cross Abstract: The rise of compound AI serving that integrates multiple operators in a pipeline enables end-user applications such as generative AI-powered m
arXiv:2604.02060v2 Announce Type: replace Abstract: When told to 'cut the cake,' a robot must choose the knife over nearby scissors, despite both objects affording the same cutting function. In real-w
This post likely discusses how meaningful work is enhanced and complemented by three key elements: the contextual environment in which work occurs, the specialized knowledge and skills brought to the
arXiv:2605.16720v1 Announce Type: new Abstract: Robust watermarking is typically trained with random post-processing augmentation, but random sampling under-covers the combinatorial space of realistic
arXiv:2601.14506v3 Announce Type: replace-cross Abstract: Large language models are increasingly deployed in STEM education for personalized instruction and feedback across institutions in high- and l
arXiv:2605.17304v1 Announce Type: cross Abstract: LLM context is not just tokens; it is a set of commitments. Long-running conversations accumulate goals, constraints, decisions, preferences, tool res
arXiv:2605.17410v1 Announce Type: new Abstract: Token economics has emerged as a useful lens for understanding resource allocation, value creation, and pricing in large language model systems. While r
Computer use turns Claude into an agent that can operate real UIs. New blog post on making it reliable in production: getting click accuracy right, choosing thinking effort levels, keeping long sessio
arXiv:2605.16405v1 Announce Type: new Abstract: Concept-bottleneck models (CBMs) are neural classifiers that compute predictions from high-level concepts extracted from the input. CBMs ensure stakehol