arXiv:2509.14963v2 Announce Type: replace Abstract: We present functions that quantify the contribution of a set of arguments in quantitative bipolar argumentation graphs to (the final strength of) an argument of interest, a so-called topic. Our set contribution functions are generalizations of existing functions that quantify the contribution of a single contributing argument to a topic. […]
DIVER: A Multi-Stage Approach for Reasoning-intensive Information Retrieval
arXiv:2508.07995v5 Announce Type: replace-cross Abstract: Retrieval-augmented generation has achieved strong performance on knowledge-intensive tasks where query-document relevance can be identified through direct lexical or semantic matches. However, many real-world queries involve abstract reasoning, analogical thinking, or multi-step inference, which existing retrievers often struggle to capture. To address this challenge, we present DIVER, a retrieval pipeline […]
Syntactic Framing Fragility: An Audit of Robustness in LLM Ethical Decisions
arXiv:2601.09724v2 Announce Type: replace-cross Abstract: Large language models exhibit systematic negation sensitivity, yet no operational framework exists to measure this vulnerability at deployment scale, especially in high-stakes decisions. We introduce Syntactic Framing Fragility (SFF), a framework for quantifying decision consistency under logically equivalent syntactic transformations. SFF isolates syntactic effects via Logical Polarity Normalization, enabling direct […]
Quantifying Self-Preservation Bias in Large Language Models
arXiv:2604.02174v1 Announce Type: new Abstract: Instrumental convergence predicts that sufficiently advanced AI agents will resist shutdown, yet current safety training (RLHF) may obscure this risk by teaching models to deny self-preservation motives. We introduce the emphTwo-role Benchmark for Self-Preservation (TBSP), which detects misalignment through logical inconsistency rather than stated intent by tasking models to arbitrate […]
MTI: A Behavior-Based Temperament Profiling System for AI Agents
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 […]