arXiv:2604.02145v1 Announce Type: new Abstract: AI models of equivalent capability can exhibit fundamentally different behavioral patterns, yet no standardized instrument exists to measure these dispositional differences. Existing approaches either borrow human personality dimensions and rely on self-report (which diverges from actual behavior in LLMs) or treat behavioral variation as a defect rather than a trait. […]
Thermodynamic connectivity reveals functional specialization and multiplex organization of extrasynaptic signaling
arXiv:2604.02057v1 Announce Type: new Abstract: Neural communication operates on both fast synaptic transmission and slower, diffusive extrasynaptic signaling, yet how these two modes jointly organize brain function remains unclear. Here, using the complete synaptic and neuropeptidergic connectomes of emphCaenorhabditis elegans, we develop a unified multiplex framework linking anatomical wiring to functional communication. We infer structure-derived […]
Strategies for tumor elimination and control under immune evasion and chemotherapy resistance
arXiv:2604.01385v1 Announce Type: new Abstract: The evolutionary and ecological dynamics of tumors under immune responses and therapeutic interventions pose major challenges to long-term treatment success. Although treatment may initially achieve short-term disease control, resistant cancer cell subpopulations often arise, leading to relapse with more aggressive and treatment-resistant forms of the disease. Here, we develop and […]
HAFixAgent: History-Aware Program Repair Agent
arXiv:2511.01047v3 Announce Type: replace-cross Abstract: Automated program repair (APR) has recently shifted toward large language models and agent-based systems, yet most systems rely on local snapshot context, overlooking repository history. Prior work shows that repository history helps repair single-line bugs, since the last commit touching the buggy line is often the bug-introducing one. In this […]
Leveraging the Value of Information in POMDP Planning
arXiv:2604.01434v1 Announce Type: new Abstract: Partially observable Markov decision processes (POMDPs) offer a principled formalism for planning under state and transition uncertainty. Despite advances made towards solving large POMDPs, obtaining performant policies under limited planning time remains a major challenge due to the curse of dimensionality and the curse of history. For many POMDP problems, […]
DVM: A Bytecode Virtual Machine Approach for Dynamic Tensor Computation
arXiv:2603.24239v2 Announce Type: replace-cross Abstract: Dynamism is common in AI computation, e.g., the dynamic tensor shapes and the dynamic control flows in models. Due to the long compilation time, existing runtime compilation damages the model efficiency, while the offline compilers either suffer from the long compilation time and device memory footprint to cover all the […]
TRU: Targeted Reverse Update for Efficient Multimodal Recommendation Unlearning
arXiv:2604.02183v1 Announce Type: new Abstract: Multimodal recommendation systems (MRS) jointly model user-item interaction graphs and rich item content, but this tight coupling makes user data difficult to remove once learned. Approximate machine unlearning offers an efficient alternative to full retraining, yet existing methods for MRS mainly rely on a largely uniform reverse update across the […]
TRACE-Bot: Detecting Emerging LLM-Driven Social Bots via Implicit Semantic Representations and AIGC-Enhanced Behavioral Patterns
arXiv:2604.02147v1 Announce Type: new Abstract: Large Language Model-driven (LLM-driven) social bots pose a growing threat to online discourse by generating human-like content that evades conventional detection. Existing methods suffer from limited detection accuracy due to overreliance on single-modality signals, insufficient sensitivity to the specific generative patterns of Artificial Intelligence-Generated Content (AIGC), and a failure to […]
Systematic Analyses of Reinforcement Learning Controllers in Signalized Urban Corridors
arXiv:2604.02025v1 Announce Type: new Abstract: In this work, we extend our systematic capacity region perspective to multi-junction traffic networks, focussing on the special case of an urban corridor network. In particular, we train and evaluate centralized, fully decentralized, and parameter-sharing decentralized RL controllers, and compare their capacity regions and ATTs together with a classical baseline […]
Diff-KD: Diffusion-based Knowledge Distillation for Collaborative Perception under Corruptions
arXiv:2604.02061v1 Announce Type: new Abstract: Multi-agent collaborative perception enables autonomous systems to overcome individual sensing limits through collective intelligence. However, real-world sensor and communication corruptions severely undermine this advantage. Crucially, existing approaches treat corruptions as static perturbations or passively conform to corrupted inputs, failing to actively recover the underlying clean semantics. To address this limitation, […]
ProCeedRL: Process Critic with Exploratory Demonstration Reinforcement Learning for LLM Agentic Reasoning
arXiv:2604.02006v1 Announce Type: new Abstract: Reinforcement Learning (RL) significantly enhances the reasoning abilities of large language models (LLMs), yet applying it to multi-turn agentic tasks remains challenging due to the long-horizon nature of interactions and the stochasticity of environmental feedback. We identify a structural failure mode in agentic exploration: suboptimal actions elicit noisy observations into […]
SEAL: An Open, Auditable, and Fair Data Generation Framework for AI-Native 6G Networks
arXiv:2604.02128v1 Announce Type: new Abstract: AI-native 6G networks promise to transform the telecom industry by enabling dynamic resource allocation, predictive maintenance, and ultra-reliable low-latency communications across all layers, which are essential for applications such as smart cities, autonomous vehicles, and immersive XR. However, the deployment of 6G systems results in severe data scarcity, hindering the […]