arXiv AI
Aug 6
SafeCommit: Certifying When Memory-Grounded Agents May Safely Act
arXiv:2608. 04289v1 Announce Type: new Abstract: Long-horizon agents increasingly use persistent memory and tools to take actions with external side effects.
AI agents
Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
arXiv AI
Aug 6
FinRpt: Dataset, Evaluation System and LLM-based Multi-agent Framework for Equity Research Report Generation
arXiv:2511. 07322v3 Announce Type: replace-cross Abstract: While LLMs have shown great success in financial tasks like stock prediction and question answering, their application in fully automating Equity Research Report generation remains uncharted territory.
arXiv AI
Aug 6
EASy: Towards Efficient LLM-Based Agentic System
arXiv:2608. 04588v1 Announce Type: cross Abstract: Agentic systems have emerged as a promising paradigm for solving complex tasks by coordinating specialized LLM-based agents.
arXiv AI
Aug 6
ZoomV: Temporal Zoom-in for Efficient Long Video Understanding
arXiv:2504. 01407v3 Announce Type: replace-cross Abstract: Long video understanding poses a fundamental challenge for large video-language models (LVLMs) due to the overwhelming number of frames and the risk of losing essential context through naive downsampling.
arXiv AI
Aug 6
ArtAnno: Annotating Implicit Semantics in Artworks through LLM Agent-Driven Bidirectional Human-AI Augmentation
arXiv:2608. 05026v1 Announce Type: cross Abstract: High-quality annotation of artworks is essential for computational art research, yet extracting implicit semantics remains challenging due to the reliance on culturally grounded meanings and deep contextual knowledge behind the images.
arXiv AI
Aug 6
Guideline-as-Oracle: Zero-Annotation Training of an Ophthalmic Telephone Triage Agent
arXiv:2608. 04772v1 Announce Type: cross Abstract: Scaling supervision for multi-turn medical agents is difficult because expert dialogue annotation is costly and clinical conversations are privacy-restricted.
arXiv AI
Aug 6
Argus: A General-Purpose Agentic Runtime for Long-Horizon Reasoning
arXiv:2608. 05144v1 Announce Type: new Abstract: Long-horizon reasoning requires an agentic runtime that can persist when evidence supports its current approach and pivot when measurements reveal failure, hidden constraints, or a misspecified objective.
arXiv Machine Learning
Aug 6
ODRA: Synthesizing Cognitive Behavioral Therapy Sessions with Structured Chain-Of-Thought and Dynamic Patient Resistance
arXiv:2608. 04524v1 Announce Type: cross Abstract: Synthetic generation of Cognitive Behavioral Therapy (CBT) sessions is challenged by two competing demands: adhering to strict therapeutic structure while modeling the resistant, unpredictable behavior of real patients.
arXiv AI
Aug 6
Scrouting: Cost-Aware Routing of Coding Agents by Scouting the Repository First
arXiv:2608. 04804v1 Announce Type: cross Abstract: Frontier language models can resolve repository-level software issues, but each attempt is expensive, and existing routers select a model from the issue text alone.
arXiv AI
Aug 6
Combating Knowledge Corruption in Agent Systems: A Byzantine-Tolerant Secure Collaborative RAG Framework
arXiv:2608. 04366v1 Announce Type: cross Abstract: While retrieval-augmented generation systems partially address the hallucination issues in large language models, it also introduces new vulnerabilities to knowledge corruption attacks.
arXiv AI
Aug 6
When Does Latent Communication Pay? A Causal Audit of Relayed KV Caches in Multi-Agent LLMs
arXiv:2608. 04893v1 Announce Type: cross Abstract: Multi-agent LLM systems relay key--value caches instead of text and credit their gains to exchanged ``latent thoughts''.
arXiv AI
Aug 6
Risk Is Not the Target: A Monotonic Framework for Evaluating Wildfire Operational Risk Signals
arXiv:2607. 21597v2 Announce Type: replace Abstract: Evaluating wildfire risk systems using standard machine-learning metrics such as F1-score or IoU is fundamentally flawed: these metrics assess event prediction accuracy, not the operational coherence of a continuous risk signal.
arXiv AI
Aug 6
Diagnosing Tool-Selection Reasoning in LLM Agents with Canary Tools
arXiv:2608. 04719v1 Announce Type: new Abstract: Agent evaluations tell us that a model picked the wrong tool, but rarely why.
arXiv AI
Aug 6
OctoLong: Mid-Training On Cross-Repository Code Contexts Enhances Long-Context Modeling
arXiv:2608. 05141v1 Announce Type: new Abstract: Context lengths of language models (LMs) have dramatically increased, driven by the demands for in-context learning, self-improvement, and long-horizon agentic workflows.
arXiv AI
Aug 6
Towards a New Grammar of Reasoning for Artificial Legal Intelligence and the Mecelle as Its Semantic Protocol
arXiv:2608. 04011v1 Announce Type: cross Abstract: This article examines the enduring epistemic and methodological crisis of traditional legal practice in light of the opportunities and constraints introduced by artificial intelligence.
arXiv AI
Aug 6
EDATracer: An Agentic Framework for Large-Scale EDA Artifact Analysis
arXiv:2608. 04032v1 Announce Type: cross Abstract: Modern chip design relies on electronic design automation (EDA) tools that generate large, heterogeneous artifacts, including source files, scripts, logs, netlists, and reports.
arXiv Machine Learning
Aug 6
Active Learning Guided Design Space Refinement for Scalable Multi-Objective Bayesian Optimization in Materials Discovery
arXiv:2608. 04651v1 Announce Type: new Abstract: Advanced materials discovery increasingly relies on machine learning and Bayesian optimization to explore large discrete design spaces under limited evaluation budgets.
arXiv Machine Learning
Aug 6
EvolveNet: Collaborative Harness Evolution for Agent Self-Improvement
arXiv:2608. 04968v1 Announce Type: new Abstract: The capabilities of an LLM agent depend not only on its model but on the harness: the executable program that constructs context, invokes tools, verifies results, and recovers from failure.
arXiv AI
Aug 6
Search, Inspect, Fetch: Exploiting Structure-Aware Boolean Retrieval for Deep-Research Agents
arXiv:2608. 02751v2 Announce Type: replace-cross Abstract: Existing deep-research agents use a Search--Visit workflow that retrieves whole webpages without considering the structure they expose through titles, headings, sections, and metadata.
arXiv AI
Aug 6
Contextual Agentic Memory is a Memo, Not True Memory
arXiv:2604. 27707v2 Announce Type: replace Abstract: Current agentic memory systems (vector stores, retrieval-augmented generation, scratchpads, and context-window management) do not implement memory: they implement lookup.