Search: “framework”

arXiv:2607.02360v1 Announce Type: cross Abstract: Monocular relative pose sensing is a central perception problem in non-cooperative rendezvous and on-orbit servicing. In spacecraft images, however, w

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Model Releases

GroundEval: A Deterministic Replacement for LLM-as-Judge in Stateful Agent Evaluation

DGX agent

arXiv:2606.22737v2 Announce Type: replace Abstract: Before letting an agent operate over real context, can you prove it used the right evidence? GroundEval turns that question into a deterministic tes

model-releasesarxiv-cs-ai

3 Jul 2026

Guided Action Flow: Q-Guided Inference for Flow-Matching Vision-Language-Action Policies

arXiv:2607.02092v1 Announce Type: cross Abstract: Flow-matching vision-language-action policies generate robot action chunks through an iterative transport process, creating an opportunity for test-ti

HAL: Inducing Human-likeness in LLMs with Alignment

arXiv:2601.02813v3 Announce Type: replace Abstract: Aligning language models to qualitative behavioral traits, such as human-likeness, remains difficult because they are hard to define, measure, and o

Hardware-Enforced Semantic Coordination for Safety-Critical Real-Time Autonomous Systems

arXiv:2607.02376v1 Announce Type: new Abstract: Recent advances in agentic AI are producing increasingly complex autonomous systems that integrate large language models, world models, optimization eng

Applications

Hawk: Harnessing Hardware-Aware Knowledge for High-Performance NPU Kernel Generation

arXiv:2607.01590v1 Announce Type: new Abstract: Developing high-performance kernels for Neural Processing Units (NPUs) is a critical industry bottleneck, requiring developers to manually navigate impl

applicationsarxiv-cs-ai

Hidden Forgetting in Continual Multimodal Learning: When Accuracy Survives but Grounding Fails

arXiv:2607.02020v1 Announce Type: new Abstract: Multimodal large language models must continually adapt to evolving tasks and domains, yet standard continual learning metrics mainly measure whether ol

Local Ai

Hybrid Diffusion Transformer for Instruction-Guided Audio Editing via Rectified Flow

arXiv:2606.20101v2 Announce Type: replace-cross Abstract: Audio editing aims to modify specific content in an existing audio clip according to a natural language instruction while preserving the remai

local-aiarxiv-cs-ai

Imagining the Sense of Touch: Touch-Informed Manipulation via Imagined Tactile Representations

arXiv:2607.01684v1 Announce Type: new Abstract: Tactile sensing can substantially improve contact-rich robotic manipulation, yet its practical deployment remains limited by the fragility, calibration

tutorialsarxiv-cs-ro

Applications

IntentTune: Using user demand and personalization to resolve 'unknown' query intents for e-commerce search

arXiv:2607.01530v1 Announce Type: cross Abstract: Understanding user intent is fundamental to delivering relevant search results in e-commerce. However, substantial fraction of real-world queries are

applicationsarxiv-cs-ai

Interpreting Global Perturbation Robustness of Image Models using Axiomatic Spectral Importance Decomposition

arXiv:2408.01139v4 Announce Type: replace Abstract: Perturbation robustness evaluates the vulnerabilities of models, arising from a variety of perturbations, such as data corruptions and adversarial a

Agents

Janus: a Playground for User-Involved Agentic Permission Management

arXiv:2607.01510v1 Announce Type: new Abstract: AI agents that autonomously execute tool calls on a user's behalf raise pressing questions about permission management: what role could users play, and

agentsarxiv-cs-ai

Kara: Efficient Reasoning LLM Serving via Sliding-Window KV Cache Compression

arXiv:2607.01237v1 Announce Type: cross Abstract: Reasoning language models often generate long chain-of-thought (CoT), which accumulates a massive KV cache during the decoding phase and incurs high d

Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution

arXiv:2508.05941v2 Announce Type: replace Abstract: Visuomotor policies trained via behavior cloning are vulnerable to covariate shift, where small deviations from expert trajectories can compound int

LearNAT: Learning NL2SQL with AST-guided Task Decomposition for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2504.02327v2 Announce Type: replace Abstract: Natural Language to SQL (NL2SQL) aims to translate natural language queries into executable SQL statements, offering non-expert users intuitive acce

Learning 3D-Gaussian Simulators from RGB Videos

arXiv:2503.24009v3 Announce Type: replace-cross Abstract: Realistic simulation is critical for applications ranging from robotics to animation. Learned simulators have emerged as a possibility to capt

tutorialsarxiv-cs-ai

Learning-based Multi-agent Race Strategies in Formula 1

arXiv:2602.23056v2 Announce Type: replace Abstract: In Formula 1, race strategies are adapted according to evolving race conditions and competitors' actions. This paper proposes a reinforcement learni

Learning Consumer Preferences from Bundle Sales Data

arXiv:2209.04942v2 Announce Type: replace-cross Abstract: Problem definition: This paper studies the problem of estimating consumer preferences from bundle sales data. Product bundling is a widely use

tutorialsarxiv-cs-lg

Learning Semantic Atomic Skills for Multi-Task Robotic Manipulation

arXiv:2512.18368v2 Announce Type: replace Abstract: Scaling imitation learning to diverse multi-task robot manipulation remains challenging due to suboptimal demonstrations, behavioral multi-modality,

Learning to Move Before Learning to Do: Task-Agnostic pretraining for VLAs

arXiv:2607.02466v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are fundamentally bottlenecked by the scarcity of expert demonstrations -- triplets of observations, instructions,

LEFT: Learnable Fusion of Tri-view Tokens for Unsupervised Time Series Anomaly Detection

arXiv:2602.08638v2 Announce Type: replace-cross Abstract: As a fundamental data mining task, unsupervised time series anomaly detection (TSAD) aims to build a model for identifying abnormal timestamps

tutorialsarxiv-cs-ai

Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation

arXiv:2607.01794v1 Announce Type: cross Abstract: With the rapid development of autonomous aerial systems, Unmanned Aerial Vehicles (UAVs) are increasingly deployed in applications such as inspection,

Locality-Aware Continual Unlearning for Diffusion Models

arXiv:2512.02657v2 Announce Type: replace-cross Abstract: Real-world deployment of text-to-image diffusion models requires continual concept removal as new privacy, copyright, or safety obligations ar

MAGIK: Mapping to Analogous Goals via Imagination-enabled Knowledge Transfer

arXiv:2506.01623v4 Announce Type: replace Abstract: Humans excel at analogical reasoning - applying knowledge from one task to a related one with minimal relearning. In contrast, reinforcement learnin

Many Voices, One Reward: Multi-Role Rubric Generation for LLM Judging and Reward Modeling

arXiv:2607.01830v1 Announce Type: new Abstract: Reliable reward and preference signals are critical for evaluating and optimizing large language models on open-ended tasks. Rubric-based judges offer a

researcharxiv-cs-lg

Mastermind: Strategy-grounded Learning for Repository-Scale Vulnerability Reproduction

arXiv:2607.01764v1 Announce Type: new Abstract: Repository-level vulnerability reproduction is a demanding software engineering (SE) task: an agent must inspect a codebase, infer the input grammar tha

Mean Field Reinforcement Learning

arXiv:2607.01525v1 Announce Type: cross Abstract: This monograph provides an introduction to mean field reinforcement learning through the lens of Markov decision processes arising from large-populati

safetyarxiv-cs-lg

MedRepBench: A Comprehensive Benchmark for Medical Report Interpretation

arXiv:2508.16674v2 Announce Type: replace-cross Abstract: Medical report understanding from real-world document images is essential for generating patient-facing explanations and enabling structured i

Memora: A Harmonic Memory Representation Balancing Abstraction and Specificity

arXiv:2602.03315v2 Announce Type: replace Abstract: Agent memory systems must accommodate continuously growing information while supporting efficient, context-aware retrieval for downstream tasks. Abs

Meta-Representational Predictive Coding: Neuroscience-Informed Self-Supervised Learning

arXiv:2503.21796v2 Announce Type: replace-cross Abstract: Self-supervised learning has become an increasingly important paradigm in the domain of machine intelligence. Furthermore, evidence for self-s

researcharxiv-cs-lg

MetaTune: Adjoint-based Meta-tuning via Robotic Differentiable Dynamics

arXiv:2603.27313v2 Announce Type: replace Abstract: Disturbance observer-based control has shown promise in robustifying robotic systems against uncertainties. However, tuning such systems remains cha

MKGR: Multimodal Knowledge-Graph Representation Learning for Cold-Start Protein-Protein Interaction Prediction

arXiv:2607.01627v1 Announce Type: cross Abstract: Accurate protein-protein interaction (PPI) prediction is central to functional genomics, disease mechanism discovery, and drug development. A difficul

MMBench-Live: A Continuously Evolving Benchmark for Multimodal Models

arXiv:2607.01813v1 Announce Type: cross Abstract: Evaluation benchmarks are essential for assessing vision-language models (VLMs), but most multimodal benchmarks are static, making them vulnerable to

Model Merging as Probabilistic Inference in Fine-Tuning Parameter Space

arXiv:2607.01689v1 Announce Type: cross Abstract: Model merging aims to combine existing single-task solutions into a multi-task solution without additional data-driven fine-tuning.~Most existing appr

Morphology-Aware Sample Assignment: Overcoming IoU Insensitivity for Surface Defect Detection

arXiv:2606.13723v2 Announce Type: replace-cross Abstract: Intersection-over-Union (IoU), as a pivotal metric for evaluating the spatial alignment between candidate proposals and ground-truth annotatio

Applications

Motion-Focused Latent Action Enables Cross-Embodiment VLA Training from Human EgoVideos

arXiv:2606.18955v2 Announce Type: replace-cross Abstract: Training generalist Vision-Language-Action(VLA) models typically requires massive, diverse robotic datasets with high-fidelity action annotati

applicationsarxiv-cs-ro

Multi-Head Recurrent Memory Agents

arXiv:2607.01523v1 Announce Type: cross Abstract: Recurrent memory agents extend LLMs to arbitrarily long contexts by iteratively consolidating input into a fixed-size memory window. Despite their sca

Multi-Objective Exploration and Preference Optimization via Mutual Information

arXiv:2607.01392v1 Announce Type: new Abstract: Aligning large language models with diverse and heterogeneous human values requires multi-objective alignment methods to effectively trade off conflicti

safetyarxiv-cs-cl

Multilingual Prompt Localization for Agent-as-a-Judge: Language and Backbone Sensitivity in Requirement-Level Evaluation

arXiv:2604.04532v2 Announce Type: replace-cross Abstract: Evaluation language is typically treated as a fixed English default in agentic code benchmarks, yet we show that changing the judge's language

NeoMap: Training-free Novel-View Synthesis from Single Images and Videos

arXiv:2607.01962v1 Announce Type: cross Abstract: We study the challenging problem of novel view video synthesis from single images or monocular videos. Existing methods, which operate under the assum

Neuron-Aware Active Few-Shot Learning for LLMs

arXiv:2607.02423v1 Announce Type: cross Abstract: Active Few-Shot Learning (AFSL) adapts LLMs to specialized domains by identifying the most valuable unlabeled samples for annotation and use as few-sh

NEUROSYMLAND: Neuro-Symbolic Landing-Site Assessment for Robust and Edge-Deployable UAV Autonomy

model-releasesarxiv-cs-ro

arXiv:2607.02277v1 Announce Type: new Abstract: Safe landing-site assessment in unstructured environments remains a key challenge for autonomous UAV deployment, as vision-only learning approaches ofte

On the Role of Computation in Reinforcement Learning

arXiv:2602.05999v4 Announce Type: replace Abstract: How does the amount of compute available to a reinforcement learning (RL) policy affect its learning? Can policies using a fixed amount of parameter

safetyarxiv-cs-lg

OntoLearner: A Modular Python Library for Ontology Learning with Large Language Models

arXiv:2607.01977v1 Announce Type: new Abstract: Ontology learning (OL) aims to automatically construct structured knowledge models from text, yet progress remains fragmented across methods, domains, a

Agents

Ophiuchus: Incentivizing Tool-augmented 'Think with Images' for Joint Medical Segmentation, Understanding and Reasoning

arXiv:2512.14157v2 Announce Type: replace Abstract: Recent medical MLLMs have made significant progress in generating step-by-step textual reasoning chains. However, they still struggle with complex c

agentsarxiv-cs-ai

Optimizing Visual Generative Models via Distribution-wise Rewards

arXiv:2607.02291v1 Announce Type: new Abstract: Conventional reinforcement learning strategies for visual generation typically employ sample-wise reward functions, yet this practice frequently results

safetyarxiv-cs-lg

Overthink-Triggered Slowdown Attacks on LVLM-Based Robotic Systems

arXiv:2607.01518v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have been increasingly integrated into robotic systems. However, these models may exhibit overthinking behaviors,

PACE: A Proxy for Agentic Capability Evaluation

arXiv:2607.02032v1 Announce Type: new Abstract: Evaluating LLM agents on benchmarks like SWE-Bench and GAIA can be expensive, time-consuming, and requires complex infrastructure. A single evaluation c