arXiv AI
Jul 28
Limbomorphs
arXiv:2607. 23842v1 Announce Type: cross Abstract: Artificial life systems are typically defined by a set of dynamical rules over an environment, an agent, or both, from which lifelike patterns may emerge.
AI agents
Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
arXiv AI
Jul 28
Commitment To Cooperation With Self-Negotiated Contracts
arXiv:2607. 22750v1 Announce Type: new Abstract: As AI agents operate with increasing autonomy in a multi-agent world, they will need to learn to cooperate with other agents and with humans to generate mutual benefits.
arXiv AI
Jul 28
SEGRA: Structured Experience-Guided Graph Reasoning Agent for Gremlin Based Question Answering
arXiv:2607. 22713v1 Announce Type: new Abstract: Enterprise IT support knowledge graphs capture rich relationships among cases, users, devices, symptoms, taxonomic categories, root causes, and historical resolutions.
arXiv Machine Learning
Jul 28
AlloBench: Measuring Online Tool Allocation Capability in LLM Agents
arXiv:2607. 23332v1 Announce Type: new Abstract: Creating a reusable tool is an investment: an agent pays a fixed cost now in exchange for the potential of future reuse.
arXiv AI
Jul 28
Mission-Level Runtime Assurance for LLM-Assisted ISR Swarms over a Verification-Aware Fabric
arXiv:2607. 23532v1 Announce Type: cross Abstract: Swarms of LLM-assisted autonomous robots are increasingly proposed for cooperative intelligence, surveillance, and reconnaissance (ISR) in contested environments.
arXiv AI
Jul 28
ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding
arXiv:2607. 24743v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundamentally a vision-centric challenge: models must absorb knowledge from heterogeneous 2D and 3D medical images, and evaluation protocols must align with radiologists' clinical practice and provide an accurate, fine-grained and factualness-driven assessment.
arXiv AI
Jul 28
Agentic Graph Retrieval-Augmented Generation for Auditable Commercial Registry Analysis
arXiv:2605. 18770v2 Announce Type: replace-cross Abstract: Public commercial registries are formally open, yet their practical analysis remains difficult because relevant facts are scattered across millions of records that combine structured metadata, multilingual legal notices, temporal events, and entity aliases.
arXiv AI
Jul 28
CodexGraph: Bridging Large Language Models and Code Repositories via Code Graph Databases
arXiv:2408. 03910v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel in stand-alone code tasks like HumanEval and MBPP, but struggle with handling entire code repositories.
arXiv AI
Jul 28
Share No More Than the Request Requires: Federated Disclosure for Perspective-Aware AI
arXiv:2607. 22953v1 Announce Type: new Abstract: Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a model where third-parties collect and control massive amounts of user data.
arXiv AI
Jul 28
Plans Work in Mysterious Ways: Evaluating a Plan Mode for Spreadsheet Agents
arXiv:2607. 23670v1 Announce Type: cross Abstract: Plan Modes have become standard features in agentic programming tools, allowing users to gain transparency and control by working with the agent to develop a plan before task execution.
arXiv AI
Jul 28
Bridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent Consensus
arXiv:2604. 13472v2 Announce Type: replace-cross Abstract: Cooperative multi-agent reinforcement learning (MARL) is widely used to address large joint observation and action spaces by decomposing a centralized control problem into multiple interacting agents.
arXiv AI
Jul 28
SkillSieve: A Hierarchical Triage Framework for Detecting Malicious AI Agent Skills
arXiv:2604. 06550v3 Announce Type: replace-cross Abstract: Agent skills combine natural-language instructions with executable code while inheriting an agent's filesystem, credential, and network access.
arXiv AI
Jul 28
The Physics of Multi-Turn Long-Horizon Planning: From Pre-training to Post-training via Single- and Multi-Teacher On-Policy Agentic Distillation
arXiv:2607. 24720v1 Announce Type: cross Abstract: Multi-turn long-horizon planning is critical for foundation model agents, yet how to fundamentally improve it remains unclear.
arXiv AI
Jul 28
Coherent Without Grounding, Grounded Without Success: Observability and Epistemic Failure
arXiv:2603. 28371v2 Announce Type: replace-cross Abstract: When an agent can articulate why something works, we typically take this as evidence of genuine understanding.
arXiv Machine Learning
Jul 28
MOCA: A Transformer-based Modular Causal Inference Framework with One-way Cross-attention and Cutting Feedback
arXiv:2604. 23107v2 Announce Type: replace-cross Abstract: Causal effect estimation from observational data requires careful adjustment for confounding.
arXiv AI
Jul 28
A didactical-driven teacher assistant for a dimensional modeling course
arXiv:2607. 22598v1 Announce Type: cross Abstract: Educational chatbots powered by large language models (LLMs) show promising effects on learning outcomes, yet most systems delegate pedagogical decisions such as content selection and didactic structuring implicitly to the LLM, making tutoring strategies difficult to trace, evaluate, and reproduce.
arXiv AI
Jul 28
EviBack: Search-Agent Reinforcement Learning via Evidence-Constrained Teacher Backoff
arXiv:2607. 23955v1 Announce Type: new Abstract: Reinforcement learning enables Agentic RAG systems to learn multi-turn search from verifiable outcome rewards, but all- zero rollout groups provide no comparative signal and may hide useful search behavior.
arXiv Machine Learning
Jul 28
GNN-based Multi-Agent Control of Traffic Shockwaves in Sparse Vehicular Ad-hoc Networks
arXiv:2607. 23792v1 Announce Type: cross Abstract: Traffic shockwaves are stop-and-go waves that propagate upstream through the streams of vehicles and are one of the major causes of traffic congestion, fuel inefficiency, and increased accident rates in modern transportation systems.
arXiv AI
Jul 28
Hybrid Advantage Estimation with Unified Critic for VLM Agentic Reinforcement Learning
arXiv:2607. 23605v1 Announce Type: new Abstract: Large Vision-Language Models (VLMs) now act as agents in interactive environments, where success requires coherent reasoning and decision-making across turns.
arXiv AI
Jul 28
Schema-Aware Localisation (SAL): Live Schema Grounding and Hallucination Validation for Oracle NL2SQL
arXiv:2607. 22572v1 Announce Type: new Abstract: Large language models can generate fluent SQL from natural language, but on real enterprise Oracle databases they frequently fail at execution time: columns and aliases are hallucinated and dialect-specific syntax is missed, leading to ORA-00904 invalid-identifier errors.