Knowledge catalogue
arXiv:2606.30934v1 Announce Type: new Abstract: Modern text-to-image diffusion models, such as diffusion transformers (DiT), rely on timestep or prompt embeddings to modulate the strength of the denoi
arXiv:2603.29135v2 Announce Type: replace Abstract: Autonomous experimental systems are increasingly used in materials research to accelerate scientific discovery, but their performance is often limit
arXiv:2507.18606v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) provides a principled framework for decision-making in partially observable environments, which can be modeled as
arXiv:2508.12413v4 Announce Type: replace-cross Abstract: The flow matching has rapidly become a dominant paradigm in classical generative modeling, offering an efficient way to interpolate between tw
This video provides a quick explanation of Retrieval-Augmented Generation Models (RLMs), outlining their benefits and demonstrating their implementation with DeepAgents. The content likely covers how
arXiv:2606.32034v1 Announce Type: cross Abstract: LLM agents increasingly act over long horizons, where a single trajectory can contain hundreds or thousands of actions. In these settings, outcome-onl
arXiv:2606.31519v1 Announce Type: cross Abstract: Long-context Large Language Model inference is severely bottlenecked by the massive Key-Value (KV) cache, yet existing sparse attention methods often
arXiv:2606.32000v1 Announce Type: cross Abstract: Why do neural networks memorize algorithmic training data long before they generalize? We present a geometric case study demonstrating that, on tasks
arXiv:2606.31801v1 Announce Type: new Abstract: Automated Heuristic Design (AHD) with Large Language Models (LLMs) has shown remarkable progress in discovering high-quality heuristics. However, existi
Artificial intelligence chipmaking startup Oxmiq Labs Inc. says it wants to become the next Arm Holdings Plc. after raising 35 million in an early-stage A funding, bringing its total amount raised to
arXiv:2606.32005v1 Announce Type: cross Abstract: Stochastic Gradient Descent (extsf{SGD}) is one of the most classical optimization algorithms with favorable theoretical guarantees, yet the practical
arXiv:2604.06687v2 Announce Type: replace Abstract: Multimodal fake news video detection is a crucial research direction for maintaining the credibility of online information. Existing studies primari
arXiv:2606.31353v1 Announce Type: new Abstract: Rotational Scanning Computed Laminography (RCL) is widely utilized for the Non-Destructive Testing(NDT) of large planar components. However, to facilita
arXiv:2606.31694v1 Announce Type: cross Abstract: For robots manipulating open-world objects, tactile representations must generalize to unseen materials. We introduce RCT (Robotic Contact Tactile), a
arXiv:2606.30778v1 Announce Type: new Abstract: Mapping a chemical reaction network, the graph of minima and transition states (TS) and the elementary reactions connecting them, is the natural languag
Together AI announced their Series C funding round, which was covered in a reporting piece by the New York Times. The announcement was shared via their official X (formerly Twitter) account, linking t
Together AI announced a Series C funding round and shared details about their company vision, current capabilities, and future direction in open-source AI development and inference optimization. The a
This post from Ollama's official X account discusses performance improvements for the Gemma 4 model, likely covering optimizations related to MLX (Machine Learning eXperimental framework) and MTP (Mul
ParallelKernelBench is a benchmark tool or methodology developed by Together AI for evaluating the performance of parallel kernel execution in machine learning systems. The benchmark likely measures m
Together AI is announcing their participation in ICML 2026 (International Conference on Machine Learning) and inviting the community to visit them at the conference. The announcement likely includes d
arXiv:2606.31834v1 Announce Type: cross Abstract: Real-world detectors for autonomous driving, surveillance, and robotics must handle domain-shifts under strict latency and memory constraints, yet exi
Really confused by all the excitement I see in my timeline for a nerfed model. Never seen anything like it. So many will end up very disappointed. Time to rethink how to build around frontier and open
arXiv:2606.31160v1 Announce Type: new Abstract: Modern Vision-Language-Action (VLA) planners for autonomous driving emit a chain-of-causation (CoC) reasoning step before producing a trajectory. The re
arXiv:2506.22075v2 Announce Type: replace Abstract: Reasoning is a hallmark of human intelligence, enabling adaptive decision-making in complex unfamiliar scenarios. In contrast, machine intelligence
arXiv:2606.31676v1 Announce Type: new Abstract: Most token reduction methods for Vision Transformers seek favorable tradeoffs between accuracy and efficiency by pruning, merging, or pooling patch toke
arXiv:2606.31055v1 Announce Type: new Abstract: Speech-to-speech (S2S) AI agents are advancing rapidly, yet evaluation lacks interpretable speech-native measures for conversational prosody and rhythm.
arXiv:2603.13057v2 Announce Type: replace Abstract: As virtual try-on (VTON) systems become increasingly important in fashion e-commerce, there is a growing need for reliable reference-free evaluation
arXiv:2506.23102v2 Announce Type: replace-cross Abstract: Current CT report generation frameworks predominantly rely on global feature representations, often failing to capture region-specific details
arXiv:2508.02187v3 Announce Type: replace-cross Abstract: 4D millimeter wave radars (4D radars) are new emerging sensors that provide point clouds of objects with both position and radial velocity mea
arXiv:2606.31392v1 Announce Type: new Abstract: Tool-augmented vision-language models (VLMs) can solve multimodal, multi-step tasks by calling external tools, yet they remain fragile in practice. Exis
arXiv:2606.31807v1 Announce Type: new Abstract: As humanoid robots become increasingly dynamic, coupling them with reinforcement learning offers a promising approach to solving the complex, underactua
arXiv:2606.32032v1 Announce Type: cross Abstract: Metacognition is a critical component of intelligence that describes the ability to monitor and regulate one's own cognitive processes. Yet LLMs exhib
arXiv:2606.31804v1 Announce Type: new Abstract: Accurate energy demand forecasting is essential for the reliable operation and planning of modern sustainable energy systems. Spatial-temporal graph neu
arXiv:2511.17442v3 Announce Type: replace-cross Abstract: Foundation Models (FMs) are increasingly integrated into remote sensing (RS) pipelines. These models include unimodal vision encoders and mult
Space Exploration Technologies Corp. showed investors and other stakeholders an early prototype of a handheld artificial intelligence device ahead of its planned initial public offering, the Wall Stre
Reselling “excess AI processing capacity”: first SPCX, now META. In a rational world these moves would be seen as signs that we have *already* started to overbuild. Boom. $META is developing a cloud s
Resend, an email API platform, has been integrated into the Vercel Marketplace, enabling developers to easily add email capabilities to their Vercel-deployed applications. This integration allows deve
arXiv:2606.31895v1 Announce Type: new Abstract: LiDAR has increasingly been integrated into traffic cameras to expand coverage and mitigate occlusion in roadside cooperative perception. However, how u
arXiv:2606.31394v1 Announce Type: cross Abstract: Artificial intelligence is transforming our capability to solve biological challenges. In dimensionality bottleneck regimes exacerbated by high-dimens
arXiv:2606.31157v1 Announce Type: new Abstract: Foundation models are increasingly integrated into embodied intelligence systems, but directly assigning them structured prediction tasks requires preci
arXiv:2511.18775v2 Announce Type: replace-cross Abstract: Virtual Try-On (VTON) synthesizes realistic images of a person wearing a target garment, with broad applications in e-commerce and fashion. Di
arXiv:2510.17139v3 Announce Type: replace Abstract: Recent advances in large language models (LLMs) have led to a surge of interest in query augmentation for information retrieval (IR). Two main appro
arXiv:2606.31249v1 Announce Type: new Abstract: In this paper, we present the solution developed by our team, XInsight Lab, which achieved first place in Track 3 of the 4th EI-MIGA-IJCAI Challenge wit
arXiv:2606.31114v1 Announce Type: new Abstract: Unmanned Traffic Management (UTM) systems are cloud-based platforms designed to manage and coordinate multiple aerial vehicles remotely. UTM systems are
arXiv:2606.31859v1 Announce Type: cross Abstract: Residual connections add every sublayer's proposed update with a fixed coefficient of one; the network never evaluates whether an update is reliable b
arXiv:2606.31446v1 Announce Type: new Abstract: RVL-CDIP is a popular dataset for benchmarking document classifiers. However, the dataset contains ample amounts of label errors as well as non-trivial
arXiv:2511.16757v2 Announce Type: replace-cross Abstract: Audio-language pretraining (ALP) holds promise for learning general-purpose audio representation, yet remains underexplored. Crucially, there
arXiv:2606.31382v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have made significant strides in embodied intelligence by integrating the powerful representations of pre-trained Vi
arXiv:2606.31282v1 Announce Type: new Abstract: Modern deep neural networks often contain far more parameters than needed to fit their training data, yet they achieve impressive generalization. A comm
arXiv:2606.30788v1 Announce Type: cross Abstract: Language models are often adapted in stages: a public skill phase, a private memory phase, and a later safety phase that learns to refuse outputs tied
arXiv:2602.03778v2 Announce Type: replace-cross Abstract: Tail-end risk measures such as static conditional value-at-risk (CVaR) are used in safety-critical applications to prevent rare, yet catastrop
arXiv:2512.24561v2 Announce Type: replace Abstract: Visual grounding (VG) localizes target objects in an image from natural-language expressions. In real-world perception, RGB cues often degrade under
arXiv:2606.31736v1 Announce Type: new Abstract: Remote photoplethysmography (rPPG) estimates physiological signals from facial videos by analyzing subtle pulse induced skin color variations. Despite r
arXiv:2606.22678v2 Announce Type: replace-cross Abstract: Agentic coding harnesses - such as Agent-Skills, Superpowers, and Agent-Rigor - are increasingly deployed to augment underlying LLMs for real-
arXiv:2606.31836v1 Announce Type: new Abstract: In the field of robot learning, large-scale and diverse demonstration trajectories provide the fundamental basis for enhancing robotic manipulation abil
arXiv:2507.11061v3 Announce Type: replace-cross Abstract: Recent advances in 3D neural representations and instance-level editing models have enabled the efficient creation of high-quality 3D content.
arXiv:2606.31613v1 Announce Type: new Abstract: Autonomous aerial inspection of marine infrastructure is frequently compromised by stochastic sea states, introducing risks of high-kinetic impacts, pos
arXiv:2606.31602v1 Announce Type: new Abstract: This work presents Dual-Embedding Watermarking (DEW), a semantic watermarking scheme for large language models (LLMs) that leverages contextual and toke
arXiv:2606.30820v1 Announce Type: new Abstract: Time Window Temporal Logic (TWTL) is a rich specification language for cyber-physical systems that can compactly express sequential tasks with explicit
arXiv:2606.31581v1 Announce Type: new Abstract: We investigate the problem of the robustness of a trained neural network to the perturbation of its input values. More specifically, we examine the inte