arXiv AI
Aug 13
Lost in Compaction: Evaluating Side-Constraint Loss under Context Compaction
arXiv:2608. 11242v1 Announce Type: cross Abstract: When the context window is under pressure, LLM systems compact prior context to continue ongoing tasks.
AI agents
Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
arXiv AI
Aug 13
Hallucination Mitigation with Agentic AI, Nested Learning, and AI Sustainability via Semantic Caching
arXiv:2605. 29055v2 Announce Type: replace Abstract: This paper describes an approach to hallucination detection and mitigation using a HOPE-inspired Nested Learning architecture with Continuum Memory Systems (CMS) and semantic similarity caching, tested on a hybrid benchmark of 310 prompts (217 epistemic-uncertainty prompts, 93 fabrication-induction stress tests).
arXiv AI
Aug 13
TMRL: Diffusion Timestep-Modulated Pretraining Enables Exploration for Efficient Policy Finetuning
arXiv:2605. 12236v2 Announce Type: replace-cross Abstract: Fine-tuning pre-trained robot policies with reinforcement learning (RL) often inherits the bottlenecks introduced by pre-training with behavioral cloning (BC), which produces narrow action distributions that lack the coverage necessary for downstream exploration.
arXiv Machine Learning
Aug 13
Diffusion-Guided Cooperative Policy Learning for Target Tracking Based on Underwater Mobile Agent Networks
arXiv:2603. 29426v2 Announce Type: replace-cross Abstract: Multi-agent reinforcement learning (MARL) provides a promising solution for cooperative target tracking in networks of autonomous underwater vehicles (AUVs).
arXiv Machine Learning
Aug 13
Better, Faster, Stronger: Programmatic Skill Learning Best Reduces Agent Cost
arXiv:2608. 11338v1 Announce Type: cross Abstract: Recently, the practice of augmenting LLM agent capability with skills has gained prevalence.
arXiv Machine Learning
Aug 13
Adaptation of Generalist Robot Policies with Minimal Data
arXiv:2608. 11363v1 Announce Type: cross Abstract: A central goal in robot learning is to move beyond task-specific human data collection toward robots that improve through autonomous interaction.
arXiv AI
Aug 13
BrowseSafe: Understanding and Preventing Prompt Injection Within AI Browser Agents
arXiv:2511. 20597v2 Announce Type: replace-cross Abstract: The integration of artificial intelligence (AI) agents into web browsers introduces security challenges that go beyond traditional web application threat models.
arXiv Machine Learning
Aug 13
High-Order Liquid Evidence Encoding for Gradual GNSS Spoofing Detection in Autonomous Driving
arXiv:2608. 11790v1 Announce Type: new Abstract: Accurate Global Navigation Satellite System (GNSS)-based localization is essential for safe and reliable autonomous driving.
arXiv Machine Learning
Aug 13
Autonomous Telerehabilitation via Skeletal Motion Prediction and Joint-Level Performance Assessment
arXiv:2608. 12145v1 Announce Type: cross Abstract: Autonomous rehabilitation systems must not only recognize human motion but also provide structured feedback to support users without continuous therapist supervision.
arXiv AI
Aug 13
TRACE Bench: Task-driven Roleplay Agentic Checklist Evaluation
arXiv:2608. 11236v1 Announce Type: cross Abstract: Roleplay evaluation should do more than assign a single score: it should reveal which role requirements were tested, which failed, and which dialogue evidence supports the judgment.
arXiv AI
Aug 13
One Frozen Simulator Is Not Enough: Simulator Collapse in Multi-Agent RL
arXiv:2608. 12253v1 Announce Type: cross Abstract: Multi-agent reinforcement learning for human-AI interaction typically relies on a single large language model to simulate user behavior.
arXiv Machine Learning
Aug 13
Achieving Near-Zero-Overhead Multi-Model Hierarchical Classification in Real-Time Detection Pipelines
arXiv:2608. 11770v1 Announce Type: cross Abstract: Edge-deployed vision systems in target recognition, surveillance, autonomous vehicles, and drone domains require hierarchical inference pipelines where a detection model identifies objects of interest and downstream classifiers provide fine-grained attribute analysis.
arXiv AI
Aug 13
HUGIN: Enhancing Vision-Language Planning for Autonomous Logistics Sorting
arXiv:2608. 11692v1 Announce Type: new Abstract: Autonomous logistics sorting systems (ALSS) are an important industrial application of embodied AI, which requires joint planning over spatially disjoint camera views.
arXiv AI
Aug 13
The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark
arXiv:2608. 11469v1 Announce Type: cross Abstract: AI agents are rapidly improving in cybersecurity capabilities when the source code is available for analysis, yet much of the software most consequential to cybersecurity, including malware, firmware, and proprietary applications, is available only as binaries.
arXiv AI
Aug 13
The Sleeping Agent: What Gist-Based Context Compression Loses and Why
arXiv:2608. 11775v1 Announce Type: new Abstract: Gist-based context compression---summarising older conversation history into compact representations---is a common approach in long-horizon language model agents, yet its effect on different types of memory retrieval is poorly understood.
arXiv AI
Aug 13
VICBench: A Multi-Language Benchmark for Code Vulnerability Detection
arXiv:2608. 12246v1 Announce Type: cross Abstract: Evaluating security vulnerability detection tools requires benchmark datasets with vulnerability-inducing commits (VICs) - the commits that first introduce vulnerabilities into codebases.
arXiv AI
Aug 13
Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence
arXiv:2608. 12290v1 Announce Type: cross Abstract: Modern black-box Image-to-Video (I2V) models offer powerful capabilities in automated content creation, yet their lack of fine-grained control and reliability presents significant challenges in professional workflows.
arXiv AI
Aug 13
Credo: Declarative Control of LLM Pipelines via Beliefs and Policies
arXiv:2604. 14401v2 Announce Type: replace Abstract: Agentic AI systems are becoming commonplace in domains that require long-lived, stateful decision-making in continuously evolving conditions.
arXiv AI
Aug 13
Semantic Lenia: Emergence of Homeostatic Solitons within the Semantic Space of Large Language Models
arXiv:2608. 11657v1 Announce Type: cross Abstract: We introduce Semantic Lenia, an artificial life framework that transforms Large Language Model (LLM) inference from a static optimization problem into a continuous dynamical system within the macroscopic logit space.
arXiv AI
Aug 13
No One to Blame: A Framework of Constitutive AI Unaccountability
arXiv:2608. 12104v1 Announce Type: cross Abstract: The increasing deployment of autonomous, agentic AI systems challenges traditional accountability mechanisms.