Can machines think efficiently?
arXiv:2510.26954v3 Announce Type: replace-cross Abstract: The Turing Test is no longer adequate for distinguishing human and machine intelligence. With advanced artificial intelligence systems already
Knowledge catalogue
arXiv:2510.26954v3 Announce Type: replace-cross Abstract: The Turing Test is no longer adequate for distinguishing human and machine intelligence. With advanced artificial intelligence systems already
arXiv:2609.00959v1 Announce Type: new Abstract: Mixed-format medical visual question answering (VQA) requires stable option selection and machine-readable free-text output. The two formats fail differ
arXiv:2609.01345v1 Announce Type: new Abstract: Inference cascades cut cost by answering most queries with a cheap model and escalating a hard tail to a frontier model that acts as verifier. A natural
arXiv:2609.00088v1 Announce Type: cross Abstract: LLM judges, models that score another system's output, can be gamed by the systems they score. Recent work identifies one defence that works: the judg
arXiv:2609.00863v1 Announce Type: new Abstract: Engineering inverse design is often limited by the high computational cost of iterative solvers for optimization problems constrained by partial differe
arXiv:2609.00804v1 Announce Type: new Abstract: Exploring unknown environments with multiple UAVs requires coordination under intermittent communication, making decentralized operation a baseline assu
arXiv:2606.14617v3 Announce Type: replace Abstract: Safe physical human--robot interaction on floating-base robots requires interaction regulation under changing contact constraints. We develop a cont
arXiv:2609.00925v1 Announce Type: cross Abstract: Language models can ignore prompt evidence when it conflicts with memorized knowledge. Post-training can make models follow such evidence more reliabl
arXiv:2512.20003v2 Announce Type: replace Abstract: Sampling from unnormalized probability densities is a pervasive challenge across the computational and physical sciences. Diffusion models provide a
arXiv:2609.00054v1 Announce Type: new Abstract: Formal Concept Analysis (FCA) is an approach for conceptual classification building and rule discovery from a binary table describing a set of objects b
arXiv:2609.00366v1 Announce Type: cross Abstract: High test accuracy and good aggregate calibration do not show whether an individual prediction is structurally supported by its evidence. In tabular d
arXiv:2609.00995v1 Announce Type: new Abstract: Recovering 3D digital humans from a single 2D image is an ill-posed computer vision problem due to the loss of depth information. Probabilistic 3D human
arXiv:2609.00272v1 Announce Type: new Abstract: Most advances in keypoint descriptions address monomodal settings, where image variations arise from viewpoint, illumination, or contrast changes. Multi
arXiv:2603.18184v2 Announce Type: replace Abstract: Interlinear glossed text (IGT) is a standard notation for language documentation which is linguistically rich but laborious to produce manually. Rec
arXiv:2012.01194v3 Announce Type: replace-cross Abstract: In this article, we introduce a deep learning based approximation algorithm for SPDEs. Our approach employs neural networks to approximate the
arXiv:2609.00885v1 Announce Type: new Abstract: Denoising diffusion models are the dominant architecture for image generation, whereas most natural language generation and modeling are primarily handl
arXiv:2609.00045v1 Announce Type: cross Abstract: Under individual smoothness, the optimal incremental first-order oracle (IFO) complexity of nonconvex finite-sum optimization has remained open. Known
arXiv:2609.00730v1 Announce Type: new Abstract: Accurate tilt angle estimation is important in many engineering applications, such as robotics, motion tracking, and embedded control systems. However,
arXiv:2609.01588v1 Announce Type: cross Abstract: Writing involves diverse cognitive activities, from ideation to revision, and writers' needs vary across individuals and moments. Proactive AI promise
arXiv:2609.00768v1 Announce Type: new Abstract: Self-play is an effective paradigm for language-model self-evolution, but without guidance, solver performance can plateau or decline across rounds. Ung
arXiv:2609.01136v1 Announce Type: new Abstract: Change captioning is the task of generating natural language descriptions that explain the changes between a pair of images. Although different change t
arXiv:2609.01449v1 Announce Type: new Abstract: Diffusion models and recursive reasoners are both iterative, but they carry information across iterations differently. We add a persistent hidden state
arXiv:2609.01370v1 Announce Type: new Abstract: Data is important in many deep learning-based inverse problem solvers. However, obtaining sufficient paired data in many scenarios remains highly challe
arXiv:2609.00644v1 Announce Type: cross Abstract: Bilevel optimization provides a natural modeling language for hierarchical decision problems. However, applying existing numerical solvers usually req
arXiv:2511.21415v2 Announce Type: replace Abstract: We introduce DiverseVAR, a framework that enhances the diversity of text-conditioned visual autoregressive models (VAR) at test time without requiri
arXiv:2609.00647v1 Announce Type: new Abstract: Multiple kernel k-means integrates complementary nonlinear similarities by learning a combination of base kernels. Its pointwise optimization, however,
arXiv:2609.00464v1 Announce Type: cross Abstract: Neuro-Symbolic (NeSy) AI has recently emerged as a novel paradigm to enable trustworthy AI, aiming at integrating sub-symbolic neural perception with
arXiv:2609.01139v1 Announce Type: new Abstract: The LLM-as-a-judge (LLMaJ) framework has emerged as a promising solution for cheap, reproducible, reference-free Natural Language Generation (NLG) evalu
arXiv:2609.01516v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) has revolutionized 3D reconstruction and novel-view synthesis, scenarios with limited input views often lead to poor
arXiv:2609.00935v1 Announce Type: cross Abstract: Deep Research agents tackle knowledge-intensive tasks through multi-round retrieval and decision-oriented generation. However, these agents suffer fro
arXiv:2609.00653v1 Announce Type: cross Abstract: Electroencephalography (EEG) is a non-invasive technique for measuring neural activity and has been widely used in neuroscience applications. Recent a
arXiv:2609.00566v1 Announce Type: cross Abstract: We propose EEG-VID, a task-guided latent predictive pretraining framework for EEG decoding under session and subject shifts. EEG-VID predicts future l
arXiv:2609.00551v1 Announce Type: cross Abstract: Multimodal memory offers a scalable interface for long-video question answering, but existing methods often retrieve captions, frames, transcripts, su
arXiv:2609.00946v1 Announce Type: cross Abstract: Conditional independence tests (CITs) test for conditional dependence between two random objects X and Y given a third random object Z. Existing CITs
arXiv:2609.00310v1 Announce Type: new Abstract: Emotional labor is the effortful management of emotional displays to meet social or professional expectations. Personality traits have been correlated w
arXiv:2606.23382v2 Announce Type: replace-cross Abstract: Transformer language models have become established tools for modeling human sentence processing, with measures such as surprisal and attentio
arXiv:2609.00023v1 Announce Type: cross Abstract: In this paper, we introduce ES-AHD, a novel framework that fundamentally integrates Evolution Strategy (ES) into Large Language Model (LLM)-driven Aut
arXiv:2609.00738v1 Announce Type: new Abstract: Inference-time search with large language models (LLMs) often concentrates on a small set of structurally or semantically similar trajectories, leaving
arXiv:2609.00994v1 Announce Type: new Abstract: Recent extensions of 3D Gaussian Splatting (3DGS) enable real-time novel view synthesis in dynamic scenes by learning time-conditioned Gaussian deformat
arXiv:2609.00629v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) achieve strong performance on image-grounded text generation and visual question answering. However, it remains dif
arXiv:2609.00539v1 Announce Type: new Abstract: Animals' body morphology shapes the gait patterns they can perform, where mechanical resonance reduces the need for active control. By tuning posture an
arXiv:2609.00097v1 Announce Type: cross Abstract: The development of long-context Large Language Models (LLMs) is constrained by the memory bandwidth bottleneck and quadratic complexity of the attenti
arXiv:2609.00543v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems rely on external corpora that may contain outdated, contradictory, noisy, or unreliable documents, introduc
arXiv:2609.00961v1 Announce Type: new Abstract: Conversational agents like chatbots and voice assistants are trained to understand and respond to user intents. On encountering an utterance with an int
Finally, a good paper testing if graph memory actually beats flat retrieval for long-term agents. (bookmark this one) Researchers extract each conversational turn into typed nodes and attributed edges
arXiv:2601.19094v3 Announce Type: replace-cross Abstract: Learning algorithmic computation often requires explicit relational intermediate states, yet many graph processors maintain their primary stat
arXiv:2609.00475v1 Announce Type: cross Abstract: Angle-encoded quantum kernels on tabular data collapse when the feature map is wider than the intrinsic dimension of the data. We propose the correlat
arXiv:2511.23120v2 Announce Type: replace Abstract: Pretrained transformers provide rich, general-purpose embeddings, which are transferred to downstream tasks. However, current transfer strategies: f
arXiv:2609.01564v1 Announce Type: cross Abstract: Large language models (LLMs) struggle to classify text into taxonomies with many semantically similar labels, as the distinctions are domain-specific
arXiv:2609.00667v1 Announce Type: cross Abstract: Large vision-language models used as listwise rerankers must jointly process visual tokens from tens of candidates per query, making token pruning ess
arXiv:2609.00948v1 Announce Type: cross Abstract: Vision-language models (VLMs) have demonstrated strong performance in visual question answering with natural images. However, they continue to struggl
arXiv:2609.01043v1 Announce Type: cross Abstract: Uniform-state discrete diffusion models update all tokens in parallel while keeping every position revisable. Even when the commonly used top-p rule l
arXiv:2609.01310v1 Announce Type: cross Abstract: Medical image segmentation remains difficult to scale because high-performing methods typically rely on dense expert annotations and task-specific tra
arXiv:2502.07584v3 Announce Type: replace-cross Abstract: Many learning algorithms can be represented as Markov processes, and understanding their generalization error is a central topic in learning t
arXiv:2606.12441v2 Announce Type: replace-cross Abstract: The four dominant learning theories of behaviorism, cognitivism, constructivism, and connectivism show significant conceptual limitations as g
arXiv:2609.00544v1 Announce Type: new Abstract: High-resolution precipitation nowcasting is critical for reducing the impacts of severe weather but remains difficult because of rapid storm evolution.
arXiv:2609.00316v1 Announce Type: new Abstract: The kinematic analysis of a generic 3R robot has been investigated with multiple approaches in the past. The algebraic approaches have established concr
arXiv:2609.01216v1 Announce Type: new Abstract: Tables are ubiquitous across diverse domains, yet reasoning over them remains a significant challenge for modern large language models (LLMs). Current a
arXiv:2609.01560v1 Announce Type: cross Abstract: We present H3-World, an efficient framework that turns the 33B MiniMax-H3 video generator into an interactive world model. Our key finding is that, as
arXiv:2609.00679v1 Announce Type: new Abstract: Reconstructing oscillatory wave fields from scattered sensors is a severely underdetermined inverse problem. Beyond the challenges of general physical-f