arXiv AI
Aug 5
Getting the Parameters Right: A Difficulty-Graded Benchmark and Probe-Guided Training for LLM Tool Calls
arXiv:2608. 03071v1 Announce Type: new Abstract: Large language model agents derive much of their capability from tool use.
Large language models
Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.
arXiv AI
Aug 5
Verifiable Memory: Learning Unified Memory Management with Local and Global Verifiers for Large Language Model Agents
arXiv:2608. 03137v1 Announce Type: new Abstract: Large language model (LLM) agents must retain reusable information, control a bounded active context, and recover earlier evidence during long-horizon interaction.
arXiv AI
Aug 5
Adversarial Stress Testing of Role-Playing Language Agents using Multi-Agent Evaluation
arXiv:2608. 03166v1 Announce Type: new Abstract: Role-Playing Language Agents (RPLAs) are increasingly deployed in high-stakes applications such as healthcare assistance, customer support, and education, where maintaining consistent personas, ethical constraints, and behavioral coherence under adversarial pressure is critical.
arXiv AI
Aug 5
The Agent Operating System (AOS): A Reference Operating Architecture for Distributed Agentic Systems
arXiv:2608. 03214v1 Announce Type: new Abstract: Large language models have transformed artificial intelligence from isolated prediction services into components of long-running, distributed systems that reason, invoke tools, retrieve external state, delegate tasks, and act on behalf of users and organizations.
arXiv AI
Aug 5
DocTrace: Towards Traceable Long Document VQA via Hierarchical Evidence Graph Reasoning
arXiv:2608. 03292v1 Announce Type: new Abstract: Long Document Visual Question Answering (LongDocVQA) requires Multimodal Large Language Models (MLLMs) to locate, integrate, and reason over heterogeneous document elements distributed across multiple pages.
arXiv AI
Aug 5
Enactive Artificial Intelligence: A Decision-Centric Architecture for Complex Systems
arXiv:2608. 03413v1 Announce Type: new Abstract: As artificial intelligence (AI) continues to evolve and mature, recent AI practices have moved beyond large language models (LLMs) and text or image generation tasks, increasingly integrating tools, agents, and harnesses to solve real business and industrial problems.
arXiv AI
Aug 5
LLaDA MoE v2: Scaling Mixture-of-Experts Diffusion Language Models
arXiv:2608. 03457v1 Announce Type: new Abstract: Diffusion language models (dLLMs) offer an alternative to autoregressive (AR) language modeling, yet the scaling behavior of Mixture-of-Experts (MoE) dLLMs remains poorly understood.
arXiv AI
Aug 5
LeanMem: Simple and Efficient Long-Term Memory for LLM Agents
arXiv:2608. 03463v1 Announce Type: new Abstract: Long-term memory is essential for LLM-based agents to sustain interactions and reliably leverage distant history.
arXiv AI
Aug 5
ChartAnno: Evaluating MLLMs for Chart Annotation Generation
arXiv:2608. 03464v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made significant progress in chart understanding, generation, and editing, but their ability to annotate existing charts remains underexplored.
arXiv AI
Aug 5
When Many Answers Are Valid, Voting Fails: Symbolic Verification for Best-of-K Causal Reasoning in LLMs
arXiv:2608. 03506v1 Announce Type: new Abstract: Self-consistency assumes the most frequent answer among sampled reasoning traces is the most reliable, but this can fail in causal reasoning: samples often repeat the same confounding error, and votes fragment across multiple valid answers, letting an invalid answer win despite a valid minority trace.
arXiv AI
Aug 5
From Social Coding to Agentic Coding: Productivity and Relational Reconfiguration in Open-Source Communities
arXiv:2608. 03585v1 Announce Type: new Abstract: Open-source software communities are a form of digital public infrastructure that not only produces code, but also generates public knowledge and interpersonal relationships through visible collaboration.
arXiv AI
Aug 5
Formal Verification of Agentic Systems over Operational Data
arXiv:2608. 03609v1 Announce Type: new Abstract: Agentic systems driven by large language models (LLMs) are increasingly deployed in real-world workflows where they act on persistent operational data.
arXiv AI
Aug 5
AutoSND: From Execution Evidence to Structural Policies for Automated Network Dismantling Heuristic Discovery
arXiv:2608. 03653v1 Announce Type: new Abstract: Network dismantling is fundamental to analyzing the robustness and vulnerability of complex systems, yet practical heuristics must balance effectiveness and computational efficiency, and are usually designed manually by researchers.
arXiv AI
Aug 5
LiveEvalBench: Toward Open-World Evaluation for Web Generation
arXiv:2608. 03689v1 Announce Type: new Abstract: Large language models are increasingly capable of synthesizing executable frontend projects, yet existing benchmarks still treat web generation as a static evaluation problem.
arXiv AI
Aug 5
When Outputs Disperse, Does Epistemic Revision Follow? A Black-Box Coupling Diagnostic for Machine Collectives
arXiv:2608. 03722v1 Announce Type: new Abstract: Collective intelligence research treats disagreement as evidence of epistemic diversity: if agents express different views, the group should retain capacity to revise.
arXiv AI
Aug 5
Agents Catching Agents: Shortcut Cascades and Benchmark Gaming in Clinical Multi-Agent Systems
arXiv:2608. 03744v1 Announce Type: new Abstract: Clinical decision support is moving toward committees of language-model agents deliberating on a shared workspace.
arXiv AI
Aug 5
Risky Business: Measuring The Faithfulness-Safety Tension
arXiv:2608. 03745v1 Announce Type: new Abstract: Chain-of-Thought (CoT) reasoning offers a promising window into model monitoring.
arXiv AI
Aug 5
ContinualSkillBench: Can LLM Agents Truly Evolve Their Capabilities?
arXiv:2608. 03874v1 Announce Type: new Abstract: Modern agent frameworks equip large language models with external skill libraries to solve complex tasks.
arXiv AI
Aug 5
When Efficiency Becomes Fragility: Exploiting Dynamic Routing Vulnerabilities in Adaptive UAV Tracking
arXiv:2608. 03902v1 Announce Type: new Abstract: Resource constraints on UAV platforms have driven a paradigm shift in aerial tracking, from pursuing performance toward balancing accuracy with efficiency.
arXiv AI
Aug 5
Interpretable Adaptive Sampling for LLM Test-Time Scaling
arXiv:2608. 03961v1 Announce Type: new Abstract: Test-time scaling improves LLM reasoning by generating and aggregating multiple candidate answers, yet many pipelines use fixed per-query budgets that spend the same compute on easy and difficult prompts.