Knowledge catalogue
arXiv:2610.00354v1 Announce Type: cross Abstract: AI agents that control wallets read attacker-reachable content, so they can be steered into proposing harmful transactions. The usual last line of def
arXiv:2602.23653v3 Announce Type: replace-cross Abstract: Large-scale Vision-Language Models (VLMs) exhibit strong zero-shot recognition, yet their real-world deployment is challenged by distribution
arXiv:2610.01320v1 Announce Type: new Abstract: Generative modeling has shown strong promise for multivariate time mseries (MTS) forecasting, especially scale to high-dimensional settings. Diffusion-b
arXiv:2512.04696v3 Announce Type: replace-cross Abstract: We develop a flexible feature selection framework based on deep neural networks that approximately controls the false discovery rate (FDR), a
arXiv:2610.00063v1 Announce Type: cross Abstract: Instance-billed serverless platforms charge for CPU and memory over the lifetime of a warm instance, making idle inference state a direct serving cost
arXiv:2610.02072v1 Announce Type: new Abstract: The study of ceramic materials constitutes a cornerstone of archaeological research, yet the post-production workflow for pottery documentation remains
arXiv:2610.01781v1 Announce Type: new Abstract: Reinforcement learning (RL) for reachability specifications is fundamental to sequential decision-making. Prior work establishes asymptotic convergence
arXiv:2610.00738v1 Announce Type: cross Abstract: The Straight-Through Estimator (STE) is a widely used heuristic for Quantization-Aware Training (QAT), but its surrogate gradients can exhibit substan
arXiv:2610.01554v1 Announce Type: new Abstract: Wanda (Sun et al., 2024) prunes large language models by scoring weights independently within each linear projection, although queries and keys interact
arXiv:2607.17384v3 Announce Type: replace Abstract: This paper provides an experimentally verified formal law for calculating the uplift that diversity of thought provides in Large Language Model (LLM
arXiv:2610.00818v1 Announce Type: new Abstract: Ambulance ramping, the delay between hospital arrival and patient handover, is a critical operational bottleneck in Emergency Medical Services (EMS), ye
arXiv:2610.01072v1 Announce Type: new Abstract: Robotic manipulation of labware is difficult when transparent or reflective objects must be identified and localized. Coded planar fiducials are a pract
arXiv:2610.01726v1 Announce Type: new Abstract: Enabling robots to estimate the kinematic parameters of articulated objects unlocks a wide range of capabilities for interaction and manipulation. The e
arXiv:2610.00577v1 Announce Type: cross Abstract: In a district-based election, N voters are partitioned into k districts, and each voter votes for one of m candidates. Each district elects a winner u
arXiv:2610.00204v1 Announce Type: new Abstract: Visual-token compression for vision--language models is posed almost entirely as a selection problem: decide which tokens to keep and discard the rest.
arXiv:2610.01297v1 Announce Type: new Abstract: Ireland's smart metering programme records electricity use at 30-minute resolution, with smart meters installed in over 80% of households as of late 202
Last month I posted a Qwen3.8-27B LoRA that makes it talk like a person instead of an assistant. It got a lot more attention than I expected: 700+ upvotes, 248 comments and 44k downloads since. I read
Hi, i got QFN running on my single r9700 but im not sure if i did everything right to get the best quality and speed out of this setup. Dont want to annoy anybody, maybe someone with the same card can
arXiv:2610.00700v1 Announce Type: new Abstract: Recent advances in AI for scientific discovery enable molecular understandingand design, yet reasoning over incomplete chemical representations remainsu
Suppose you’re recording a human plugging a cable into a socket to collect demonstrations for robot learning. The hand tracker captures the approach accurately. Then occlusion causes the hand estimate
arXiv:2610.00405v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) perform strongly across forecasting tasks, but their per-series inference is ill-suited to neighbor-rich forecasti
arXiv:2610.00541v1 Announce Type: cross Abstract: Recursive models create computational depth through parameter reuse, offering a parameter-efficient alternative to increasing model size. However, mos
arXiv:2610.01548v1 Announce Type: new Abstract: As the use of large language models (LLMs) expands, post-training has become increasingly important for adapting them to downstream tasks. However, obta
arXiv:2610.01969v1 Announce Type: new Abstract: Concept erasure aims to remove a target concept, such as a copyrighted style, a recognizable character, or unsafe content, from a pretrained text-to-ima
arXiv:2610.00927v1 Announce Type: new Abstract: We study episodic adversarial linear constrained Markov decision processes (CMDPs) with unknown transitions, where both the loss and constraint function
arXiv:2610.01344v1 Announce Type: cross Abstract: Reinforcement learning offers the prospect of a reusable sequential decision-making mechanism for spacecraft trajectory design, motivating policy inte
arXiv:2610.00064v1 Announce Type: new Abstract: Assembly actions are compositional: they combine a manipulation with a part or tool. In deployment, systems routinely encounter novel combinations of fa
arXiv:2610.00823v1 Announce Type: new Abstract: We present a planning and control approach to reactively use hand contacts to stabilize a humanoid in low stability scenarios, where only using feet con
arXiv:2603.26945v2 Announce Type: replace Abstract: Appearance-based gaze estimation (AGE) has achieved remarkable performance in constrained settings, yet we reveal a significant generalization gap w
arXiv:2610.00897v1 Announce Type: new Abstract: We propose a human-factor-aware method of allocating robot supervision tasks to multiple human operators. In scenarios where multiple operators occasion
arXiv:2610.00220v1 Announce Type: new Abstract: Real-time motion generation for tendon-driven continuum robots requires accurate modeling of nonuniform bending and whole-body collision avoidance. This
arXiv:2610.01780v1 Announce Type: new Abstract: A companion that talks with a person for months should come to understand them. It should remember what they said, infer who they are, and know when the
arXiv:2610.00724v1 Announce Type: cross Abstract: Language models learn content and style jointly, making stylistic variation in their outputs difficult to identify and control. We study whether recur
arXiv:2606.13607v3 Announce Type: replace Abstract: When large language models (LLMs) fail to generalize or make content-sensitive errors in reasoning, it is often taken as evidence that LLMs are not
arXiv:2610.01184v1 Announce Type: cross Abstract: Remote multimodal models offer strong numerical reasoning capabilities over charts and speech, but sending private inputs risks exposing sensitive con
arXiv:2610.01612v1 Announce Type: new Abstract: Continuous legged manipulation requires accurate end-effector tracking while the base keeps walking. Combining reinforcement learning (RL) with model pr
arXiv:2610.02204v1 Announce Type: cross Abstract: Building reliable robot capabilities across diverse tasks requires substantial human effort to develop and maintain skills, design rewards, and integr
arXiv:2610.01178v1 Announce Type: new Abstract: Manipulation failures can leave scenes in states from which a task policy cannot recover. Learning corrective behaviors requires scalable failure explor
Recursive Language Models: Claude Code, Agent Swarms, Big Research Bets, & the $40M AI Problem Solver https://www.latent.space/p/rlm MIT’s @a1zhang explains why Claude Code, Codex, and Pi are basicall
arXiv:2508.08882v5 Announce Type: replace Abstract: Recent advances in multi-agent systems highlight the potential of specialized small agents that collaborate via division of labor. Existing tool-int
arXiv:2610.00558v1 Announce Type: new Abstract: While Mixture-of-Experts (MoE) models effectively scale model capacity through sparse activation, their deployment is often bottlenecked by prohibitive
arXiv:2610.00730v1 Announce Type: new Abstract: Mixed-integer linear programs (MILP) model many real-world decision problems, motivating machine-learning methods that exploit recurring structure to ac
arXiv:2610.00320v1 Announce Type: cross Abstract: Fine-tuning adapts aligned large language models (LLMs) to downstream tasks, but a few dozen harmful examples can remove their refusal of harmful requ
arXiv:2504.10416v3 Announce Type: replace Abstract: Autonomous exploration for mapping unknown large scale environments is a fundamental challenge in robotics, with efficiency in time, stability again
arXiv:2610.00940v1 Announce Type: cross Abstract: We propose ReHoPER, an inference-only, zero-shot method that improves large language models' reasoning by generating and answering intermediate questi
arXiv:2610.01546v1 Announce Type: cross Abstract: Primal-dual hybrid gradient (PDHG) methods solve large-scale linear programs (LPs) using GPU-friendly matrix-vector products and projections, but thei
arXiv:2610.00970v1 Announce Type: cross Abstract: Recent advances in 3D reconstruction have progressed from per-scene optimization to feed-forward inference, and semantic scene understanding has follo
arXiv:2610.02033v1 Announce Type: new Abstract: Individual mobility trajectories support urban analysis and location-based services, yet most trajectory generators require observations from their depl
arXiv:2610.00996v1 Announce Type: new Abstract: Reliable roll prediction of unmanned surface vehicles (USVs) is essential for ensuring navi?gational safety and enhancing autonomous decision-making. Wh
arXiv:2610.01725v1 Announce Type: new Abstract: Tabular foundation models achieve state-of-the-art performance on single-table tasks without any training. Recent work suggests that they are also well-
arXiv:2610.00710v1 Announce Type: new Abstract: As large language model (LLM) agents become widely adopted, they are increasingly deployed for tasks that require persistent monitoring or recurring act
arXiv:2610.01728v1 Announce Type: cross Abstract: Understanding loss landscapes is central to explaining neural-network training, yet their structure remains only partially understood even in simple m
arXiv:2610.00348v1 Announce Type: cross Abstract: Backdoor attacks can be implanted in Large Language Models (LLMs) during training, causing unwanted behaviour when a trigger appears in the input. Exi
Amazon.com Inc. reportedly plans to offload some of its artificial intelligence chips and then lease them back. The Financial Times today cited sources as saying that the transaction would involve a s
arXiv:2610.00400v1 Announce Type: cross Abstract: Multi-turn attacks on agentic systems can compose individually permissible actions into harmful outcomes, challenging defenses that assess actions or
arXiv:2610.01453v1 Announce Type: new Abstract: Deep neural networks are increasingly deployed in long-lived systems, where task requirements may change after training. In such settings, part of the o
arXiv:2610.01222v1 Announce Type: new Abstract: As generative AI (Gen AI) systems take on increasingly autonomous roles in economically and socially consequential interactions, understanding their pro
arXiv:2610.01140v1 Announce Type: new Abstract: Sampling multiple solutions spends computation on intermediate deductions and unfinished arguments as well as final answers. We introduce ReSolve, a tra
arXiv:2610.01206v1 Announce Type: new Abstract: Partially transmissive screens and protective covers are common in robotic inspection, but they create mixed LiDAR returns from both the foreground mate
arXiv:2601.22434v2 Announce Type: replace-cross Abstract: Training generative machine learning models to produce synthetic tabular data has become a popular approach for enhancing privacy in data shar