Stories tagged science & research.
The Quantum Insider / Quantum Computing Report
CGI and D-Wave have partnered to bring quantum optimization solutions to enterprises, integrating D-Wave's quantum hardware into CGI's IT services. This collaboration aims to develop quantum-powered applications for complex challenges in transportation, logistics, and retail, leveraging CGI's…
The Quantum Insider / Quantum Computing Report
A global study conducted by various international quantum industry consortia found that 90% of quantum companies rely on cross-border supply chains for hardware and software, with 74% serving international customers. The report, based on data from 160 quantum enterprises across 15 countries…
The Quantum Insider / Quantum Computing Report
An independent benchmark on IBM Heron hardware evaluated commercial quantum error management tools. Q-CTRL and Qedma QESEM significantly reduced errors compared to IBM's native Qiskit Runtime, with Qedma achieving the highest precision at a higher QPU time cost, while Q-CTRL offered a balance of…
The Quantum Insider / Quantum Computing Report
Q-CTRL has successfully executed the Quantum Fourier Transform (QFT) on up to 100 qubits using a novel Convolutional Compilation Strategy, demonstrating the largest functional QFT on quantum hardware to date. This method eliminates routing overhead on linear nearest-neighbor topologies by…
Economic Times — Tech / Technology / Startups / ETTelecom
US artificial intelligence startup Anthropic on Wednesday unveiled the first discovery from its molecular biology lab, a previously unknown enzyme system spotted by its Claude model and touted by the company as proof that AI can speed up basic research. Anthropic said its researchers' involvement…
arXiv
arXiv:2609.20278v2 Announce Type: replace-cross Abstract: Current Transformer interfaces index tokens by one or more integer coordinates, which determine their addresses inside attention. In RoPE and its multi-axis or hierarchical variants, the resulting address has the form…
arXiv
arXiv:2605.21292v2 Announce Type: replace-cross Abstract: Unbiased stochastic gradients can match the full gradient in expectation while changing finite-step stability. We study this effect in one-layer linear self-attention for in-context linear regression, where shared-mode mini-batch training…
arXiv
arXiv:2609.26579v1 Announce Type: cross Abstract: A central concern with language models is sycophancy: their tendency to defer to users' views at the expense of independent substantive judgment. In parallel, work on social sycophancy has focused on behaviors such as validation and positivity that…
arXiv
arXiv:2609.25980v1 Announce Type: cross Abstract: Probabilistic time series foundation models (TSFMs) provide coordinate-wise predictive distributions, but these marginals do not determine a joint distribution over multivariate future trajectories. We study training-free coupling of frozen TSFM…
arXiv
arXiv:2609.26059v1 Announce Type: new Abstract: Course-of-action (COA) generation is a distributed planning problem: a system must propose structured candidate actions, evaluate them against an adversarial response, and surface options that remain tactically coherent under changing conditions. We…
arXiv
arXiv:2609.25647v1 Announce Type: new Abstract: Predicting early outcomes based on trajectory can decrease the expenses associated with agent evaluation by terminating a run once the outcome becomes sufficiently predictable, assuming that the predictor's confidence is properly calibrated…
arXiv
arXiv:2609.26637v1 Announce Type: cross Abstract: The rapid capability gains of frontier language models are widely attributed to improved reasoning abilities, yet this cannot be verified as raw CoT traces in closed-source systems are hidden. By registering a simple custom tool through a standard…
arXiv
arXiv:2607.13049v2 Announce Type: replace Abstract: Foundation models give robots powerful high-level reasoning, yet turning that intelligence into reliable physical action remains difficult: roboticists must still align device drivers, network interfaces, sensors, controllers, and safety…
arXiv
arXiv:2606.04111v2 Announce Type: replace-cross Abstract: Vision-based UAV navigation becomes challenging when navigation targets are distributed across complementary camera views and cannot be reliably observed from a single viewpoint. We propose AgenticDiffusion, an agentic multi-view UAV…
arXiv
arXiv:2606.26383v2 Announce Type: replace-cross Abstract: How fast could a deep-learning model run on target hardware, and how far is today's implementation from that limit? These questions are central to software, hardware, and algorithm optimizations. Speed-of-Light (SOL) analysis answers them by…
arXiv
arXiv:2607.18496v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used for a range of software, hardware and human-centered security tasks. Consequently, LLM performance on security tasks is an active area of measurement and research, often with a focus on…
arXiv
arXiv:2608.25922v2 Announce Type: replace-cross Abstract: GNN-based Knowledge Graph Question Answering (KGQA) pipelines process queries through four discrete stages: entity linking, subgraph retrieval, GNN reasoning, and answer generation. Standard robustness evaluations conflate stage-level…
arXiv
arXiv:2609.14570v2 Announce Type: replace-cross Abstract: Multi-agent LLM systems combine multiple inference calls, but prior work often confounds how calls are connected with how they are diversified. We study these factors independently: inference topology and source of inter-agent diversity. In…
arXiv
arXiv:2609.19399v2 Announce Type: replace-cross Abstract: Game-theoretic analyses of cyber defence often compute equilibria of games whose payoffs exist only as the output of a simulator. Iterative equilibrium-finding methods grow a set of attacker and defender policies and need the payoff of every…
arXiv
arXiv:2609.22178v2 Announce Type: replace-cross Abstract: Computer-use agents (CUAs) have made rapid progress in completing complex tasks through graphical user interfaces, yet post-training centered on task success alone does not induce reliable safety behavior. A reliable CUA must condition its…
arXiv
arXiv:2609.23466v2 Announce Type: replace-cross Abstract: Long-running LLM agents require memory that persists and evolves across sessions. Text-based memory retrieves and reconstructs past interactions at every query, making long-horizon performance increasingly dependent on retrieval quality and…
arXiv
arXiv:2609.25891v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) often struggle with fine-grained visual perception when processing complete images, as critical evidence may only appear in local regions. On-policy self-distillation (OPD) enables transferring privileged…
arXiv
arXiv:2609.26007v1 Announce Type: cross Abstract: Monocular drone navigation requires reaching a goal in an unseen environment from a single forward-facing camera, which offers few cues for depth and scale. World models address this by modelling how observations evolve under actions, but they are…
arXiv
arXiv:2609.26039v1 Announce Type: cross Abstract: Point cloud generation has emerged as a crucial task for accurately capturing and reproducing the complexity of the physical world. However, existing generative approaches, predominantly relying on Transformers and Variational Autoencoders (VAEs)…
arXiv
arXiv:2609.26204v1 Announce Type: cross Abstract: When a professional web developer's code fails a test, they do not simply re-read the stack trace. They open the application in a browser, click buttons, inspect computed styles, and run diagnostic commands to understand what went wrong. Existing…
arXiv
arXiv:2609.26295v1 Announce Type: cross Abstract: The mobility sector is undergoing a paradigm shift driven by advances in Generative Artificial Intelligence. With a global market valued at approximately 2.9 trillion dollars annually, considering only cars, the integration of these technologies has…
arXiv
arXiv:2609.26355v1 Announce Type: cross Abstract: Reinforcement learning has become a central component of large language model (LLM) post-training, yet token-level credit lacks a generally accepted mathematical definition, leaving its relationship to commonly used training signals unclear. We…
arXiv
arXiv:2609.26486v1 Announce Type: cross Abstract: Automatic lip-synchronous dubbing requires a speech synthesis model to generate alternating voice and silence patterns in the target language that match the timing of the source clip precisely to ensure an optimal viewing experience. Prior works…
arXiv
arXiv:2609.26527v1 Announce Type: cross Abstract: When two texts describe the same expression, standard metrics based on lexical overlap or whole-text similarity may fail to detect meaningful differences in how that expression is framed. We propose a framework to evaluate semiotic alignment between…
arXiv
arXiv:2502.16396v2 Announce Type: replace-cross Abstract: Federated learning systems are increasingly threatened by data poisoning attacks, where malicious clients compromise global models by contributing tampered updates. Existing defenses often rely on impractical assumptions, such as access to a…