Knowledge catalogue
arXiv:2609.12384v1 Announce Type: new Abstract: This work investigates the control strategies of complex whole-body robot teleoperation that coordinate active perception, bimanual manipulation, and na
arXiv:2609.11986v1 Announce Type: cross Abstract: Passive acoustic monitoring produces far more bat recordings than experts can label. We show that simple model-generated pseudo-labels turn this surpl
arXiv:2609.12168v1 Announce Type: new Abstract: Visual Question Answering (VQA) systems, jointly interpreting images and natural language queries, hold significant promise across many domains, yet the
arXiv:2609.12793v1 Announce Type: new Abstract: Stock price prediction remains challenging due to the non-stationary and noisy nature of financial time series. Existing deep learning models often rely
arXiv:2609.12853v1 Announce Type: cross Abstract: The widespread adoption of data-driven, energy-efficient model predictive control (MPC) in buildings remains hindered by substantial effort to collect
arXiv:2609.12875v1 Announce Type: new Abstract: Machine olfaction trains on pooled public descriptor corpora, but whether a shared descriptor word measures the same thing across corpora has not been t
arXiv:2606.21203v2 Announce Type: replace Abstract: Psycholinguistics studies show that human readers fall for coherence illusions: an incoherent discourse can seem coherent simply because a distracto
arXiv:2609.12702v1 Announce Type: new Abstract: Capturing the digital trace of handwriting usually requires a specific stylus and a compatible substrate, be it a capacitive touchscreen, an ElectroMagn
【AIの難問は、生命の難問へ：英国王立協会が紐解く「世界モデル」と知能の未来】 近年のAIの急速な発展により、AGI、すなわち人間並みの知能はすでに実現したという意見も聞かれるようになりました。果たしてそうなのでしょうか。 鍵となるのが「世界モデル（World Model）」の概念です。 世界モデルとは、生き物やAIが外の世界を内部に写し取り、次に何が起きるかを予測して行動するための土台となるもの
I must be among an extremely small group of people (n=1?) that have both 1) trained a frontier LLM and 2) designed and synthesized custom viruses in a lab with my own two hands. And I think that the t
Investors in Anthropic founded Open Philanthropy, the leading org promoting AI Doom They have a stake in regulation on AI that excludes competitors OP is the major funder of Tarbell Tarbell Fellows pe
Looped transformers are a popular architecture topic right now. This new technical report extends the loop across tokens. Recurrent Looped Transformer (RLT) makes the decoder recurrent over every toke
arXiv:2609.10579v1 Announce Type: cross Abstract: We present a machine-checked Lean~4 formalization of Dong and Yang's classification of optimal finite-length (n,4) binary block codes for binary symme
arXiv:2609.11713v1 Announce Type: cross Abstract: Artificial neural networks rely on vector-matrix multiplications (VMMs), whose implementation in von Neumann architectures is dominated by costly data
arXiv:2609.11498v1 Announce Type: new Abstract: Practical uncertainty quantification (UQ) for large language models must decide, from a single generation, whether a specific answer should be trusted.
arXiv:2609.11224v1 Announce Type: cross Abstract: Sports data analysts translate domain questions into insights by combining computation with sport-specific domain expertise. Large language models eas
arXiv:2609.10707v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) into Security Operations Centers (SOCs) streamlines threat intelligence but introduces critical vulner
arXiv:2609.11115v1 Announce Type: new Abstract: Benchmark researchers and developers of large language models (LLMs) and other AI systems need to find relevant evaluations, locate their benchmark data
I’ve been researching which models to sub to and I’m currently not subbed to anything. I’ve definitely searched here and other places for opinions but a lot of what I was reading wasn’t current or 6mo
arXiv:2609.11170v1 Announce Type: new Abstract: Temporal graph counterfactual explanations typically change past events to change or invalidate an original prediction, while leaving its replacement un
arXiv:2609.11446v1 Announce Type: new Abstract: Heterogeneous model collaboration seeks to exploit the complementary strengths of different models to balance predictive performance and inference cost.
arXiv:2607.09489v2 Announce Type: replace Abstract: An AI system's output is not the fact or world state it appears to describe, but rather an engineered representation. We propose a semantic framewor
arXiv:2609.11404v1 Announce Type: cross Abstract: This paper presents DF-CAPTCHA, an active defense against real-time deepfake impersonation in voice and video calls. Instead of passively searching fo
arXiv:2506.14045v2 Announce Type: replace Abstract: Developing agents capable of exploring, planning and learning in complex open-ended environments is a grand challenge in artificial intelligence (AI
arXiv:2609.11341v1 Announce Type: new Abstract: Multimodal brain state decoding has largely focused on fusing paired modalities for prediction, but has rarely explored how their correspondence can be
arXiv:2609.11182v1 Announce Type: cross Abstract: In classical pattern recognition tasks, neural networks are trained to recognise human-defined patterns for model inputs. Some Explainable AI (XAI) me
arXiv:2609.11509v1 Announce Type: new Abstract: Quantifier instantiation is currently the main approach to non-ground SMT solving: solvers generate ground instances and solve the resulting ground SMT
arXiv:2603.29944v3 Announce Type: replace-cross Abstract: Quantum sensing technologies offer transformative potential for ultra-sensitive biomedical sensing, yet their clinical translation remains con
arXiv:2604.06015v2 Announce Type: replace Abstract: Instruction tuning is commonly assumed to endow language models with a domain-general ability to follow instructions, yet the underlying mechanism r
I love this and really hope we can come together as an industry and make it happen. We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan
arXiv:2609.11447v1 Announce Type: cross Abstract: This work investigates a number of approaches to prevent catastrophic forgetting in class incremental learning scenarios for sound event classificatio
arXiv:2609.11066v1 Announce Type: cross Abstract: In conversational AI, detecting when a speaker has finished talking is crucial for natural turn taking. While recent work incorporates semantics, the
arXiv:2609.11319v1 Announce Type: new Abstract: Most of mathematical knowledge has been communicated through so-called informal use of mathematics and natural language. With large language models (LLM
arXiv:2609.11876v1 Announce Type: new Abstract: Recently, a wide range of recommendation algorithms inspired by deep learning techniques have emerged as the performance leaders on several standard rec
arXiv:2603.09309v3 Announce Type: replace Abstract: Verbalized confidence, in which LLMs report a numerical certainty score, is widely used to estimate uncertainty in black-box settings, yet the confi
arXiv:2609.11452v1 Announce Type: new Abstract: Efficient routing optimization is essential to freight transportation, urban logistics, and shared mobility, where high-quality heuristics are often req
arXiv:2609.11315v1 Announce Type: new Abstract: Diffusion vision-language models generate answers through iterative refinement, exposing intermediate answer trajectories that can be inspected and cont
arXiv:2609.11667v1 Announce Type: cross Abstract: In this paper, we develop warrant theory as a philosophical discipline concerned with the inferential legitimacy of propositions within logical analys
arXiv:2609.11211v1 Announce Type: cross Abstract: Deep learning models, notably Long Short-Term Memory (LSTM), have demonstrated promising performance in channel estimation for high-mobility vehicular
arXiv:2609.11894v1 Announce Type: new Abstract: Solving novel view synthesis (NVS) for millimeter-wave (mmWave) radar requires a renderer that is physically faithful, complex-valued, and multi-viewpoi
arXiv:2609.11550v1 Announce Type: new Abstract: Early diagnosis of melanoma is critical for improving patient survival rates. However, accurately distinguishing melanoma from other skin lesions remain
arXiv:2609.06470v2 Announce Type: replace-cross Abstract: To solve the fractional knapsack problem, Dantzig's greedy rule orders items according to their value-to-cost ratio. This ordering introduces
arXiv:2609.10654v1 Announce Type: cross Abstract: The Abstraction and Reasoning Corpus (ARC) benchmarks cognitive generalization, the ability to infer and apply abstract rules from limited examples. T
arXiv:2609.11188v1 Announce Type: new Abstract: Synthetic image attribution (SIA) has become increasingly important with the rapid advancement of text-to-image generation models. However, accurately i
arXiv:2609.10729v1 Announce Type: cross Abstract: Quantum-inspired classical algorithms have dequantized several quantum machine learning routines by replacing quantum linear-algebra subroutines with
arXiv:2609.11299v1 Announce Type: cross Abstract: We propose an all-reflective two-mirror projection system for extreme ultraviolet (EUV) lithography operating at exposure wavelengths of 13.5~nm (Mo/S
arXiv:2609.10983v1 Announce Type: cross Abstract: Stress localization in heterogeneous solids is governed by the bimaterial interface, where the displacement field remains C^0-continuous, while in-pla
arXiv:2604.05519v2 Announce Type: replace-cross Abstract: Active noise cancellation (ANC) is widely deployed on consumer headphones and earbuds to suppress environmental noise. However, existing ANC s
arXiv:2609.10752v1 Announce Type: new Abstract: Standard cross-entropy loss causes neural networks trained on ordinal classification tasks to hedge predictions toward center classes, a failure mode we
arXiv:2511.17475v2 Announce Type: replace-cross Abstract: Neural network subgrid stress models often have a priori performance that is far better than the a posteriori performance, leading to neural n
arXiv:2603.27325v2 Announce Type: replace Abstract: Accurate wound classification (WC) and boundary segmentation are essential for guiding clinical decisions in chronic and acute wound management. How
arXiv:2509.24425v2 Announce Type: replace Abstract: The proliferation of Internet-of-Things (IoT) devices has led to an unprecedented volume of multivariate time series (MTS) data, requiring efficient
arXiv:2609.11472v1 Announce Type: new Abstract: Reliable non-rigid point cloud correspondences are important for deformable anatomical registration, embodied perception and manipulation, and dynamic 3
arXiv:2609.10647v1 Announce Type: new Abstract: We study the application of federated learning (FL) to indoor fire detection. Such fire-detection systems use edge cameras that record sensitive footage
arXiv:2606.19468v2 Announce Type: replace Abstract: The narrative composition of web-scale LLM pretraining corpora remains largely unexplored, even though narrative is a fundamental mode of human comm
arXiv:2509.22360v2 Announce Type: replace Abstract: Large language models (LLMs) excel at operating at scale by leveraging social media and various data crawled from the web. Whereas existing corpora
arXiv:2609.11071v1 Announce Type: cross Abstract: Quantum reservoir computing (QRC) uses quantum dynamics to represent input histories for prediction through a trained classical readout. Discrete time
arXiv:2609.11545v1 Announce Type: new Abstract: Low-resource multilingual text-to-speech (TTS) systems have expanded language coverage, but their robustness under complex text inputs remains insuffici
arXiv:2609.10737v1 Announce Type: new Abstract: Conformal prediction converts point predictions into set-valued predictions with coverage guarantees under exchangeability between calibration and deplo
arXiv:2609.10778v1 Announce Type: new Abstract: Machine learning models can achieve strong test performance while relying on demographic or acquisition-related shortcuts. We propose counterfactual (CF