CIG: Exploration via Conditional Information Gain
arXiv:2605.20878v1 Announce Type: new Abstract: Intrinsic rewards for exploration in reinforcement learning condition on different contexts: lifelong rewards score each transition against accumulated
Knowledge catalogue
arXiv:2605.20878v1 Announce Type: new Abstract: Intrinsic rewards for exploration in reinforcement learning condition on different contexts: lifelong rewards score each transition against accumulated
arXiv:2605.21372v1 Announce Type: new Abstract: Data scaling is fundamental to modern deep learning, and grows increasingly critical as autonomous driving shifts to end-to-end learning. Real-world dri
arXiv:2605.21157v1 Announce Type: new Abstract: In modern warfare, drones are becoming an essential part of intelligence gathering and carrying out precise attacks in different kinds of hostile enviro
arXiv:2602.08686v2 Announce Type: replace Abstract: Prefill-only KV compression freezes a token subset at the end of prefill and decodes from it without further eviction. The retention decision is the
arXiv:2605.20270v1 Announce Type: new Abstract: A local specialist LLM, fine-tuned with reinforcement learning from verifiable rewards (RLVR) on operator-local data, is installed in a regulated organi
arXiv:2605.20696v1 Announce Type: new Abstract: Preference-based reinforcement learning (RL) is a key paradigm for aligning policies with human judgments, yet its theoretical behavior in distributed s
arXiv:2605.20920v1 Announce Type: new Abstract: Recent advances in machine learning and the availability of articulatory datasets allow vocal tract synthesis to be conditioned on phonetic sequences, a
arXiv:2605.21303v1 Announce Type: new Abstract: Mechanistic interpretability produces circuit-level causal analyses of neural network behaviour, but discovered circuits often remain isolated experimen
arXiv:2605.20727v1 Announce Type: new Abstract: Deep neural networks (DNNs) experience significant performance degradation when processing noisy labels, primarily due to overfitting on mislabeled data
arXiv:2605.20362v1 Announce Type: new Abstract: Virtual staining of histopathology images (e.g., H&E-IHC) is an emerging tool in digital pathology, enabling faster and cheaper workflows by synthesizin
arXiv:2605.21475v1 Announce Type: new Abstract: Relational prediction tasks are fundamental in many real-world applications, where data are naturally stored in relational databases (RDBs). Relational
arXiv:2605.20258v1 Announce Type: new Abstract: Contextual Integrity (CI) defines privacy not merely as keeping information hidden, but as governing information flows according to the norms of a given
The unit of AI compute has shifted from single hosts to rack-scale systems that integrate NVIDIA GPUs, CPUs, scale-up networking fabrics, and liquid cooling, such as the NVIDIA GB300 NVL72 and NVIDIA
arXiv:2605.21160v1 Announce Type: new Abstract: The discovery of first integrals is of fundamental scientific importance for understanding conservation laws in dynamical systems. However, existing sym
arXiv:2605.20735v1 Announce Type: new Abstract: This paper proposes two new open-source iris recognition algorithms, providing both Python and IREX-compliant C++ implementations to be submitted to the
arXiv:2603.01406v2 Announce Type: replace Abstract: Neural PDE solvers are often described as learning solution operators that map problem data to PDE solutions. In this work, we argue that this inter
arXiv:2605.20818v1 Announce Type: new Abstract: In this report, we present our champion solutions for the Natural Language Queries and GoalStep tracks of the Ego4D Episodic Memory Challenge at CVPR 20
arXiv:2605.20496v1 Announce Type: cross Abstract: The Strong Platonic Representation Hypothesis suggests that representational convergence in artificial neural networks can be harnessed constructively
arXiv:2605.20867v1 Announce Type: cross Abstract: Multimodal sarcasm detection requires reasoning over cross-modal incongruities between literal expression and intended meaning, yet the specific analy
arXiv:2605.21454v1 Announce Type: new Abstract: We introduce ProtoPathway, an interpretable-by-design multimodal framework for cancer survival prediction that unifies whole slide imaging and transcrip
arXiv:2509.24725v3 Announce Type: replace Abstract: Estimating queue lengths at signalized intersections is a long-standing challenge in traffic management. Partial observability of vehicle flows comp
🚀Qwen3.7-Max just landed at 56.6 on the Artificial Analysis Intelligence Index — a solid 4.8pt jump over Qwen3.6-Max-Preview. @ArtificialAnlys ⚡️Sharper sci reasoning, stronger agentic chops, better c
arXiv:2605.21211v1 Announce Type: cross Abstract: In this work we present an efficient and practically implementable approach for the application of reinforcement learning (RL)-based control in chemic
arXiv:2509.22963v3 Announce Type: replace Abstract: Reinforcement learning (RL) struggles to scale to large, combinatorial action spaces common in many real-world problems. This paper introduces a nov
arXiv:2605.21237v1 Announce Type: new Abstract: Cardiac motion over a cardiac cycle is crucial for quantifying regional function and is strongly affected by cardiovascular diseases. Since temporally d
arXiv:2605.20708v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have become a de facto backbone of modern visual generation, and nearly every major axis of their design -- tokenization,
arXiv:2605.20919v1 Announce Type: new Abstract: Sutra is a typed, purely functional programming language whose compiled forward pass is a PyTorch neural network. The compiler beta-reduces the whole pr
arXiv:2510.06063v2 Announce Type: replace-cross Abstract: Modern enterprises generate vast streams of time series metrics when monitoring complex systems, known as observability data. Unlike conventio
arXiv:2509.07674v2 Announce Type: replace Abstract: Explainability, in particular, the ability for robots to explain why they have made a decision or behaved in a certain way, is a critical tool in he
arXiv:2605.20946v1 Announce Type: new Abstract: The thinking-while-speaking paradigm aims to make AI communication more human. A key challenge is maintaining fluent speech while performing deep reason
arXiv:2605.21442v1 Announce Type: new Abstract: Modern LLMs typically require multistage training pipelines to achieve strong downstream performance, with post-training serving as the main interface f
arXiv:2605.21032v1 Announce Type: new Abstract: High-fidelity street scene reconstruction is pivotal for end-to-end autonomous driving simulation, where novel-view synthesis (NVS) and time-varying inf
arXiv:2605.20599v1 Announce Type: new Abstract: This study presents a comprehensive approach for the clustering and classification of upper-limb surface electromyography (sEMG) signals during function
arXiv:2605.20364v1 Announce Type: new Abstract: Automatic evaluation of long-form literary writing remains challenging, as generic LLM-as-Judge approaches may not fully capture creativity-related dime
arXiv:2603.13609v2 Announce Type: replace Abstract: Despite progress in deep learning for shared micromobility demand prediction, the systematic design and statistical validation of temporal input str
arXiv:2605.18798v1 Announce Type: new Abstract: We propose non-parametric estimators for the average run length (ARL) and average detection delay (ADD) in quickest changepoint detection (QCD) under fi
arXiv:2605.18839v1 Announce Type: cross Abstract: Overcrowding in emergency departments (ED) remains a persistent operational challenge worldwide, causing delays in care delivery and downstream conges
arXiv:2605.19043v1 Announce Type: cross Abstract: Automated grading systems have enabled scalable assessment for many response types, but handwritten mathematics remains a barrier due to the complexit
b9253 is the latest version of llama.cpp, released on May 20, 2026. Llama.cpp is a project for LLM inference in C/C++. This build includes bug fixes, performance improvements, and features for running
arXiv:2505.16819v4 Announce Type: replace Abstract: Recent advances in scene-based video generation enable coherent visual narratives from structured prompts, yet a key aspect of storytelling -- chara
arXiv:2605.19132v1 Announce Type: new Abstract: The electrocardiogram (ECG) is the gold standard for non-invasive diagnosis of cardiac pathologies and is a fundamental pillar of cardiovascular medicin
arXiv:2605.18916v1 Announce Type: cross Abstract: We investigate Counterfactual Video Foley Generation, which aims to adopt a sound-source identity that contradicts the visual evidence while remaining
arXiv:2605.19887v1 Announce Type: cross Abstract: Current Physical AI (PAI) relies heavily on closed-loop visual-servoing pipelines, whose perception and planning stages may become computationally int
deepagents v0.6 ships w/ support for code interpreters! these are the perfect happy medium between pure tool execution and heavyweight sandboxes they give your agent an environment where it can... → k
arXiv:2605.19294v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies are typically deployed with asynchronous inference: the robot executes a previously predicted action chunk while
arXiv:2605.19557v1 Announce Type: cross Abstract: We study post-hoc Learning to Defer (L2D) through the lens of ideal distributions: divergence-regularized reweightings of the data distribution under
arXiv:2506.12218v2 Announce Type: replace-cross Abstract: Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architec
arXiv:2605.18881v1 Announce Type: new Abstract: In dynamic flow fields, various animals exhibit remarkable odor search capabilities despite relying on stochastic detections. Interestingly, there exist
arXiv:2605.19842v1 Announce Type: new Abstract: We propose a scalable tensorization framework for neural network compression based on slice-wise feature distillation. Unlike conventional tensor decomp
arXiv:2605.19279v1 Announce Type: new Abstract: Visual image reconstruction from functional Magnetic Resonance Imaging (fMRI) is a fundamental task in brain decoding, providing a crucial pathway for u
arXiv:2601.18993v2 Announce Type: replace-cross Abstract: Camera redirection aims to replay a dynamic scene from a single monocular video under a user-specified camera trajectory. However, large-angle
arXiv:2511.16062v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) excel on homophilous graphs but often fail under heterophily due to self-reinforcing and phase-inconsistent signals. We
arXiv:2605.19050v1 Announce Type: new Abstract: Generating stable molecular conformations typically forces a tradeoff between the physical realism of energy-based relaxation and the sampling efficienc
arXiv:2605.19889v1 Announce Type: cross Abstract: 3D Lookup Tables (3D LUTs) are widely used for color mapping, but their grid-based representation requires discretizing the RGB space, leading to a ca
arXiv:2605.20138v1 Announce Type: new Abstract: This article presents a Hamilton--Jacobi (HJ) reachability framework for a two--satellite collision avoidance problem operating in the same circular orb
arXiv:2605.19902v1 Announce Type: new Abstract: Predicting protein-ligand binding affinity remains intractable for multi-domain proteins, where inter-domain dynamics govern molecular recognition. Exis
arXiv:2605.18932v1 Announce Type: cross Abstract: In this work, we propose HypergraphFormer, a novel and efficient approach to floor plan generation based on learning hypergraph representations with a
arXiv:2605.20159v1 Announce Type: new Abstract: Non-destructive testing of aerospace SiC/SiC composites via X-ray computed tomography (XCT) relies on expert visual assessment, with current workflows o
Lambda Labs announced a partnership with Hudson River Trading (HRT), a quantitative trading firm, to provide computational infrastructure and GPU resources for HRT's quantitative research and developm
arXiv:2605.19113v1 Announce Type: cross Abstract: Many clinical risk scores are deployed as additive rules with nonnegative integer points assigned to relevant binary predictive features. These intege