Knowledge catalogue
arXiv:2607.12939v1 Announce Type: new Abstract: Point tracking in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, aut
arXiv:2607.12417v1 Announce Type: new Abstract: Although vast amounts of data, such as audio signal spectra, are naturally represented using complex numbers, conventional machine learning methods ofte
arXiv:2607.12341v1 Announce Type: new Abstract: Text-to-SQL is increasingly deployed across trust boundaries between data providers and users. Such deployment must balance three competing requirements
arXiv:2607.10560v2 Announce Type: replace-cross Abstract: Mesh deformation, the process of altering the vertex positions of a 3D mesh while preserving its topological structure, is a cornerstone of co
arXiv:2607.12755v1 Announce Type: cross Abstract: AI-enabled systems are seeing increasing deployment across numerous domains, with many being 'black boxes' with respect to core functions and capabili
arXiv:2601.11443v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has emerged as a powerful approach for enhancing large language models' question-answering capabilities through
arXiv:2607.11899v1 Announce Type: cross Abstract: High-altitude Clear Air Turbulence (CAT) poses significant risks to aviation safety due to its unpredictability and challenges in detection. This stud
arXiv:2607.11327v2 Announce Type: replace-cross Abstract: Model editing keeps large language models (LLMs) up to date without retraining, but temporal facts expose a limitation of the prevailing locat
arXiv:1809.01898v2 Announce Type: replace-cross Abstract: The growing complexity of software calls for innovative solutions that support the deployment of reliable and secure software. Machine Learnin
arXiv:2607.12335v1 Announce Type: new Abstract: Prototype-based networks provide inherently interpretable classification by linking predictions to learned exemplars, but their use in 3D point clouds a
arXiv:2607.12246v1 Announce Type: new Abstract: Personalization in two-sided marketplaces relies heavily on user-level features, yet for platforms with infrequent, high-consideration purchases, a larg
arXiv:2607.11916v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with evolutionary computation has emerged as a powerful paradigm for automated heuristic design in com
arXiv:2603.27270v2 Announce Type: replace Abstract: Credal sets, i.e., closed convex sets of probability measures, provide a natural framework to represent aleatoric and epistemic uncertainty in machi
arXiv:2607.12269v1 Announce Type: new Abstract: We introduce Quantum Port-Hamiltonian Neural Networks (Q-pHNNs), a family of parameterised quantum circuits that learn classical dynamics in a structure
arXiv:2607.11936v1 Announce Type: new Abstract: Hyperdimensional Computing (HDC) represents symbols using high-dimensional hypervectors of dimension D. In hypervector decomposition, the objective is t
arXiv:2607.12334v1 Announce Type: new Abstract: Retrieval-augmented question answering depends on selecting evidence passages that jointly support answer generation. However, many RAG pipelines rely o
arXiv:2607.11019v2 Announce Type: replace Abstract: Enterprise data analysis is emerging as a distinct frontier for autonomous agents. Compared with general-purpose interaction and software engineerin
arXiv:2505.12682v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly released under restricted licenses, creating a growing need for robust model ownership verification. E
arXiv:2607.12903v1 Announce Type: new Abstract: In operational 1:N face identification, a crucial question arises for each probe: is this person enrolled in the gallery or not? The stakes are high and
arXiv:2607.12216v1 Announce Type: cross Abstract: Multi-agent and memory-augmented LLM systems often place coordination content, shared state, prior discussion, tool outputs, summaries, and role instr
Frontier models are just so good though. Fable 5... Gemini 3.1 Pro for design critique and brainstorming. Grok for verification passes. Antigravity with Gemini 3.5 Flash for rote plan execution. Openc
arXiv:2607.12909v1 Announce Type: cross Abstract: Falling detection is vital for elderly care and intelligent surveillance; however, prevailing vision-based approaches predominantly frame it as static
arXiv:2508.19186v2 Announce Type: replace-cross Abstract: Reactive obstacle avoidance methods often cause agents to become trapped in local minima, because they can often only reason one step ahead (i
arXiv:2607.12495v1 Announce Type: new Abstract: Creating photorealistic 3D assets requires bridging the appearance gap between real-world observations and synthetic models. A promising approach is to
Some fixes & boost(pp) for SYCL/Intel. Merged PRs: [SYCL] Flash Attention with XMX engine via oneDNN graph API (SDPA) on KV f16 for Xe2 ; Qwen3.6-27b-Q8_0 prefill speed up x1.21 at p=512 and x4.26 at
arXiv:2607.10541v2 Announce Type: replace-cross Abstract: Sequential recommender systems typically infer user preferences through single-pass encoding of interaction histories without iterative refine
arXiv:2607.12391v1 Announce Type: new Abstract: We present a diffusion based model for asynchronous time series prediction, where the goal is to predict the next inter event time and event type. To ad
arXiv:2607.12354v1 Announce Type: new Abstract: In this paper, we challenge the prevailing view that information dependency (including rote memorization) drives training data exposure to image reconst
arXiv:2607.12287v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models exhibit strong generalization for robotic manipulation, yet their high inference latency limits real time deployment
arXiv:2607.12680v1 Announce Type: new Abstract: Existing vision-language navigation methods often couple a VLM with waypoint decoders to produce multi-step action plans, but they typically lack an exp
arXiv:2607.09759v2 Announce Type: replace-cross Abstract: Building assistants that can continually watch the world, remember what they see, and reason over their accumulated experience is a long-stand
arXiv:2607.12206v1 Announce Type: new Abstract: We present RegHead, a framework for constructing semantic blendshape sets for animatable non-humanoid head avatars. With a fixed expression vocabulary,
arXiv:2603.24787v2 Announce Type: replace Abstract: Routing has emerged as a promising strategy for balancing performance and cost in large language model (LLM) systems that combine lightweight models
arXiv:2607.11983v1 Announce Type: cross Abstract: A specialist tolerates blind spots that a generalist does not. Usually this is treated as a cost to be minimized. We treat it as a design variable: a
arXiv:2607.11928v1 Announce Type: new Abstract: Single-shot fringe projection profilometry (FPP) networks that regress depth directly can exploit a shape-prior shortcut, recovering depth from object b
arXiv:2607.12052v1 Announce Type: cross Abstract: Synthetic image attribution aims at identifying the generator responsible for a given AI-generated image. Training-free reference-based attribution me
arXiv:2607.12097v1 Announce Type: new Abstract: Video games are a dynamic medium experienced over time. While there are many Procedural Content Generation (PCG) approaches for generating video game le
arXiv:2607.12840v1 Announce Type: cross Abstract: Unconventional computing systems must demonstrate robust performance under real-world environmental conditions to enable practical deployments. We hav
arXiv:2607.11193v2 Announce Type: replace-cross Abstract: To ensure the overall quality of AI-enabled software, not only traditional software components but also AI components need to be tested and re
arXiv:2603.22510v2 Announce Type: replace-cross Abstract: Large language models are increasingly used in scholarly work, yet it remains unclear whether their productivity gains are accompanied by chan
arXiv:2607.12985v1 Announce Type: new Abstract: Aligned language models routinely misreport under non-evidential incentive pressure: they agree with a confident user or overstate certainty even when t
arXiv:2603.14217v3 Announce Type: replace Abstract: In cognitive science and linguistic theory, dialogue is not seen as a chain of independent utterances but rather as a joint activity sustained by co
arXiv:2510.00492v3 Announce Type: replace Abstract: The reliability of large language models (LLMs) during test-time scaling is often assessed with external verifiers or reward models that distinguish
arXiv:2607.12227v1 Announce Type: new Abstract: We revisit the evaluation of automatic harness evolution for LLM agents. Existing harness evolution methods use unit test cases to search for harness co
arXiv:2607.12753v1 Announce Type: new Abstract: Image super-resolution (ISR) has witnessed remarkable progress with diffusion models and flow matching. The dominant text-to-image (T2I) based approache
arXiv:2607.12395v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards without human-annotated data, often referred to as zero RL, has emerged as a powerful paradigm for elicit
arXiv:2512.04144v3 Announce Type: replace Abstract: Targeted interventions on language models, such as unlearning or model editing, aim to modify specific information, but their effects often propagat
Disclosure: I work at Pluralis Research, the lab that built this. Code is open, and I'm happy to answer questions. TL;DR: As far as we can tell, this is the first RL post-training run whose entire rol
arXiv:2503.06796v2 Announce Type: replace Abstract: Robot design is a complex and time-consuming process that requires specialized expertise. Gaining a deeper understanding of robot design data can en
arXiv:2507.11498v3 Announce Type: replace Abstract: Humanoid robots have seen remarkable advances in dexterity, balance, and locomotion, yet their role in expressive domains such as music performance
arXiv:2607.12337v1 Announce Type: cross Abstract: With the growing demand for satellite sensing and communication, the limited wireless resources are difficult to support multiple satellite systems. T
arXiv:2607.12105v1 Announce Type: cross Abstract: In-hand manipulation without external sensing is challenging due to uncertainties from finger-object contacts and disturbances by gravity. While reinf
arXiv:2607.12954v1 Announce Type: cross Abstract: Engineering use of AI forecasting models requires not only high nominal accuracy but also predictable behavior under uncertain inputs. In photovoltaic
arXiv:2607.12245v1 Announce Type: new Abstract: Few-shot industrial defect detection remains difficult for standard supervised detectors, which achieve poor performance on boundary-dominated industria
arXiv:2603.01568v2 Announce Type: replace-cross Abstract: Efficient coding theory predicts that biological perceptual systems compress sensory input optimally under resource constraints, with the syst
arXiv:2607.12360v1 Announce Type: new Abstract: The cooldown phase of a warmup-stable-decay (WSD) learning-rate schedule, now a default in large-model pretraining, lowers the final training loss in so
arXiv:2607.12488v1 Announce Type: new Abstract: Molecular optimization in drug discovery, materials design, and catalysis requires searching vast chemical spaces under tight evaluation budgets, since
arXiv:2511.11470v3 Announce Type: replace Abstract: 3D urban generation from satellite imagery is an important task for scalable digital twins and real-world simulation environments. Existing approach
arXiv:2607.12266v1 Announce Type: new Abstract: Mixed-precision quantization must decide which parts of a model to keep at higher precision. A common premise, shared by sensitivity-based methods such
arXiv:2607.11952v1 Announce Type: new Abstract: Network alignment identifies node correspondences across different networks and is a fundamental primitive in many data science applications, including