Knowledge catalogue
arXiv:2608.25500v1 Announce Type: cross Abstract: Reusable skill libraries allow large language model (LLM) agents to reuse procedural knowledge across tasks, but they also turn memory access into a c
arXiv:2608.24947v1 Announce Type: new Abstract: End-to-end training of multimodal neural networks often exhibits unstable neural dynamics characterized by three coupled failure modes that degrade lear
arXiv:2608.25871v1 Announce Type: new Abstract: Forecasting in large-scale e-commerce marketplaces is increasingly required to support planning: merchants need to evaluate sales outcomes under future
arXiv:2608.25917v1 Announce Type: cross Abstract: Game-theoretic models provide principled frameworks for modeling vehicle interactions, but their underlying temporal assumptions have not been systema
CHRISTMAS IS HERE BIG ANNOUNCEMENT FROM HUGGING FACE TODAY: We're unveiling Microduck 🐥🤖 It's a tiny $399 open-source robot you can teach new tricks with reinforcement learning. It can walk, pick thin
I installed the Claude Desktop via the ollama Mac app. Unfortunately, no connectors or plugins can be installed or none are listed. Is that normal or is there no possibility there submitted by /u/amne
arXiv:2608.24974v1 Announce Type: new Abstract: AI-based structured interference rejection has grown more popular because deep learning approaches can outperform traditional methods by jointly conside
arXiv:2608.25692v1 Announce Type: new Abstract: Generalized Category Discovery (GCD) is an intriguing open-world problem that has garnered increasing attention: given partially labelled data, the goal
arXiv:2608.25531v1 Announce Type: new Abstract: Humanities and social science research requires close reading of long narrative materials such as novels, scripts, archives, and case reports, yet many
arXiv:2512.10032v3 Announce Type: replace Abstract: Finding cause-effect relationships is of key importance in science. Causal discovery aims to recover a graph from data that succinctly describes the
arXiv:2608.25927v1 Announce Type: cross Abstract: World models aim to simulate how complex environments evolve under actions and events, yet existing video-based world models primarily learn dynamics
Cohere's Chief AI Officer @jpineau1 has been named to this year's TIME 100AI list, recognizing the world's most influential people in artificial intelligence. Joelle has been shaping modern research i
@ComfyUI is now the first and only commercial license distributor for @MiniMax_AI's generative media models. Which means you can train on them, on your own data. A foundation model's training data is
arXiv:2608.24964v1 Announce Type: cross Abstract: This note studies the geometry of full conformal prediction (FullCP) regions generated by an empirical energy-form pairwise score. Candidate-score con
arXiv:2608.25745v1 Announce Type: new Abstract: A key result in statistics is the data processing inequality, originally proved by Blackwell (1951) and later refined by DeGroot (1962) in terms of stat
arXiv:2608.25505v1 Announce Type: cross Abstract: Motivated by parallel decoding in masked diffusion models, we study adaptive parallel sampling of discrete vectors: in each round, a deterministic pol
arXiv:2608.25572v1 Announce Type: new Abstract: Action-conditioned world models have become an important foundation for embodied prediction, planning, and synthetic data generation, but their errors u
Instinct, the developer of an artificial intelligence assistant popular among Silicon Valley tech workers, is reportedly raising 250 million in funding. The company told the Wall Street Journal on Wed
arXiv:2606.14005v2 Announce Type: replace Abstract: Feature fusion networks are fundamental components in modern object detectors, aggregating multi-scale features to detect objects of varying sizes.
arXiv:2608.25932v1 Announce Type: cross Abstract: Three-dimensional probabilistic inversion of time-domain airborne electromagnetic (AEM) data is limited by the cost of the forward solve. Even though
arXiv:2608.25171v1 Announce Type: new Abstract: Soft pneumatic actuators offer inherent compliance and safe interaction but remain difficult to model and control because of their highly nonlinear, dis
arXiv:2608.25569v1 Announce Type: new Abstract: Large Language Models (LLMs) often produce emotionally flattened responses after alignment, limiting their effectiveness in affect-sensitive application
arXiv:2608.25930v1 Announce Type: cross Abstract: Control variables are widely used in statistical modelling to account for omitted variable bias of known confounders. However, they have largely been
arXiv:2608.25794v1 Announce Type: new Abstract: Federated Learning (FL) enables distributed training of machine learning models while preserving data privacy. However, FL struggles with heterogeneous,
arXiv:2608.25344v1 Announce Type: new Abstract: Perceived risk in driving evolves over time and may be supported by specific scene entities, yet supervision is typically limited to coarse video-level
arXiv:2608.25370v1 Announce Type: cross Abstract: Sequential recommendation models, while powerful, have limited flexibility in responding to immediate user requests, making it difficult to adapt thei
arXiv:2608.25192v1 Announce Type: new Abstract: We introduce CRESSim-Neo, a batched GPU simulation engine for surgical robotics and robot learning. CRESSim-Neo combines position-based simulation of ri
arXiv:2608.25539v1 Announce Type: new Abstract: A plant-health score can appear precise while resting on duplicated image families, a long-tailed label space, or a runtime file that was never evaluate
arXiv:2608.25579v1 Announce Type: new Abstract: Metaphor-identification performance can change markedly across datasets that differ in text distribution and annotation policy. We examine whether a fix
arXiv:2608.25568v1 Announce Type: new Abstract: To reduce deployment cost and retraining overhead, adapting pretrained learned image compression (LIC) models to downstream machine vision tasks has att
arXiv:2608.25023v1 Announce Type: cross Abstract: Multimodal product models can complete missing e-commerce attributes, yet current methods still optimize attribute-answer accuracy without verifying v
arXiv:2608.24987v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) distills several domain-expert teachers into a single student by minimizing per-domain reverse-KL divergence
arXiv:2608.25421v1 Announce Type: cross Abstract: The Stochastic Simulation Algorithm (SSA), widely considered an exact algorithm for stochastic chemical reaction networks, suffers from high computati
arXiv:2608.25061v1 Announce Type: new Abstract: GPUs increasingly accelerate database systems, but query-specific peak performance still often relies on hand-written kernels. Existing LLM kernel bench
arXiv:2608.25635v1 Announce Type: new Abstract: Industrial e-commerce search systems ultimately aim to optimize the user-level long-term objective, such as n-day cumulative purchases or gross merchand
arXiv:2608.25428v1 Announce Type: new Abstract: Correcting flawed reasoning traces remains a significant challenge for Large Language Models (LLMs), whose autoregressive generation can propagate early
arXiv:2608.25480v1 Announce Type: new Abstract: Dataset distillation compresses a large training set into a compact synthetic set while preserving its downstream utility. However, existing methods pri
arXiv:2505.15661v2 Announce Type: replace Abstract: Gradient-based learning imposes (deep) neural networks to be differentiable at all steps. This includes model-based architectures constructed by unr
arXiv:2608.25675v1 Announce Type: new Abstract: Objective: Diffusion-weighted MRI (DWI-MRI) is the gold standard for visualizing and quantifying acute ischaemic stroke (AIS). Although deep learning me
Self-hosted speech AI carries an observability trade-off: the numbers that drive capacity planning and cost management stay locked inside the vendor container. Deepgram closes that gap on Amazon SageM
Spent yesterday getting Qwen3.8 Flash and GLM 5.3 Flash up and running on my cluster of 4 x DGX Sparks with a view to replacing DeepSeek 0731... but.. really not that impressed with GLM 5.3 - overly v
arXiv:2608.25851v1 Announce Type: new Abstract: Self-supervised learning (SSL) encoders are vulnerable to backdoor attacks, posing threats to both visual SSL encoders and vision-language encoders. Exi
arXiv:2608.25073v1 Announce Type: new Abstract: Digital mobility outcomes (DMOs) derived from wearable sensors characterise mobility in daily life and offer a promising means of monitoring disease pro
arXiv:2608.24949v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training has emerged as a powerful framework for enhancing the capabilities of large language models (LLMs), enabling
Need a low-cost, high-performance way to run long-lived, stateful workloads such as AI agents? Today, we introduced Cloud Run instances, which let you do just that. Consider AI agents such as OpenClaw
arXiv:2608.26002v1 Announce Type: new Abstract: Advanced automation is a key technology for enhancing the safety of ground operations amidst the increasing density of commercial air traffic. While mot
arXiv:2608.24901v1 Announce Type: new Abstract: A decodable 'empathy' direction is routinely read as a causal lever, conflating decodability, automated-metric control, and human-perceived change. We t
arXiv:2608.25222v1 Announce Type: new Abstract: The impairment of the hands can seriously affect the abilities of every individual to perform the every-day activity, so the design of stable and contro
Didn't update on ik_llama.cpp updates for sometime. Updates from this month: cuda : repair the HIP build, and validate IQ4_KS and IQ4_KT on RDNA3- #2339 vulkan : add IQ4_KS and IQ4_KT support- #2332 I
arXiv:2404.11754v4 Announce Type: replace Abstract: This paper focuses on reducing the communication cost of federated learning by exploring generalization bounds and representation learning. We first
arXiv:2608.25710v1 Announce Type: new Abstract: Data augmentation is a standard component of modern semantic segmentation pipelines, but most augmentation techniques allocate transformations uniformly
arXiv:2608.25652v1 Announce Type: new Abstract: We present RoofDiT, a generative framework for 2D roof graph synthesis and reconstruction. Roofs are compactly described as planar graphs of junctions a
arXiv:2608.25429v1 Announce Type: cross Abstract: Machine unlearning aims to make a model forget specific data, yet unlearned LLMs often fail to stay unlearned: brief fine-tuning can revive removed kn
arXiv:2608.25999v1 Announce Type: new Abstract: Linguistic meaning is grounded in conceptual content, from which reference to particular entities emerges as words enter discourse. To examine the proce
arXiv:2608.25876v1 Announce Type: cross Abstract: Generative design interfaces increasingly expose semantic controls that let users steer output with concepts such as 'more elegant' or 'more minimalis
arXiv:2608.24988v1 Announce Type: new Abstract: Activation steering can be embedded directly into a language model's weights, shaping behaviour without inference-time intervention and offering a way t
arXiv:2608.25773v1 Announce Type: new Abstract: Understanding user preferences from noisy and temporally evolving social media behaviors is fundamentally challenging due to interest drift, where user
arXiv:2608.25138v1 Announce Type: new Abstract: Stochastic masking, cropping, or modality removal makes deterministic reconstruction an incomplete target: one observation can admit many clean completi
arXiv:2608.26019v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) uses a privileged copy of the student model to provide dense supervision without an external teacher. OPSD keeps this
arXiv:2608.24904v1 Announce Type: new Abstract: Inertial sensors at multiple body locations can improve activity recognition, but requiring every sensor at inference increases the deployment burden. W