Clay weekly context brief for the Computer Science category (ISO week 2026-W31).

Clay tracks publications from the Computer Science feed list. Below are recent items from this category, each with its source and a short description of what the publication covers when one is available in the source feed.

Recent publications:
1. On the Runtime Analysis of Reinforcement Learning Hyper-Heuristics
   Source: cs.NE (Neural and Evolutionary Computing)
   Link: https://arxiv.org/abs/2607.22036
   Selection Hyper-heuristics (HHs) automate algorithmic design by selecting from a set of low-level heuristics which one to apply at each stage of the optimisation process.
2. A Unified Framework for Automated Assembly Sequence and Production Line Planning using Graph-based Optimization
   Source: cs.MS (Mathematical Software)
   Link: https://arxiv.org/abs/2512.13219
   This paper presents PyCAALP (Python-based Computer-Aided Assembly Line Planning), a framework for automated Assembly Sequence Planning (ASP) and Production Line Planning (PLP), employing a graph-based approach to model components and joints within production modules.
3. Participatory Budgeting with Project Groups
   Source: cs.MA (Multiagent Systems)
   Link: https://arxiv.org/abs/2012.05213
   We study a generalization of the standard approval-based model of participatory budgeting (PB), in which voters are providing approval ballots over a set of predefined projects and---in addition to a global budget limit, there are several groupings of the projects, each group with its own budget limit.
4. LeAct: Learning to Reason from Expert Actions
   Source: cs.LG (Machine Learning)
   Link: https://arxiv.org/abs/2607.21856
   Modern reasoning models depend on reasoning data, today sourced from human annotations or distilled from stronger LLMs.
5. Simpson's Paradox in Behavioral Curves: How Aggregation Distorts Parametric Models of User Dynamics
   Source: cs.IR (Information Retrieval)
   Link: https://arxiv.org/abs/2605.11017
   Behavioral curve modeling -- fitting parametric functions to engagement-versus-exposure data -- is standard practice in recommendation, advertising, and clinical dosing.
6. Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases
   Source: cs.DB (Databases)
   Link: https://arxiv.org/abs/2602.09572
   The purpose of predictive modeling on relational data is to predict future or missing values in a relational database, for example, future purchases of a user, risk of readmission of the patient, or the likelihood that a financial transaction is fraudulent.
7. Can AI Debias the News? LLM Interventions Improve Cross-Partisan Receptivity but LLMs Overestimate Their Own Effectiveness
   Source: cs.CY (Computers and Society)
   Link: https://arxiv.org/abs/2605.01006
   Partisan news media erode cross-partisan trust, but large language models (LLMs) offer the potential of debiasing such content at scale.
8. FAIR: Feature-Augmented Implicit Regularization for AI-generated Fake Image Detection
   Source: cs.CV (Computer Vision and Pattern Recognition)
   Link: https://arxiv.org/abs/2607.22087
   Generalization remains a critical bottleneck in AI-generated image detection.
9. MEUSLI: a Multilingual Projector for LLM-based ASR and Beyond
   Source: cs.CL (Computation and Language)
   Link: https://arxiv.org/abs/2607.22100
   Lightweight projectors are an established way to connect pre-trained speech encoders with large language models (LLMs), mapping acoustic features into token-level embeddings for tasks like ASR and spoken question answering.
10. A Theoretical Framework for Environmental Similarity and Vessel Mobility as Coupled Predictors of Marine Invasive Species Pathways
   Source: cs.CE (Computational Engineering, Finance, and Science)
   Link: https://arxiv.org/abs/2511.03499
   Marine invasive species spread through global shipping and generate substantial ecological and economic impacts.
11. On the Advantage of Adaptivity for Sampling with Cell Probes
   Source: cs.CC (Computational Complexity)
   Link: https://arxiv.org/abs/2605.12873
   We construct an explicit distribution $\mathbf{D}$ over $\{0,1\}^N$ that exhibits an essentially optimal separation between adaptive and non-adaptive cell-probe sampling.
12. Dynamic Rowhammer Threshold Management:Temperature-Aware Threshold Degradation for In-DRAM Defenses
   Source: cs.AR (Hardware Architecture)
   Link: https://arxiv.org/abs/2607.10392
   In-DRAM Rowhammer defenses pin the mitigation threshold at manufacture time, yet the true Rowhammer Threshold (TRHD) varies with runtime temperature.
13. Discrete Action Space as a Prerequisite for GRPO Convergence in Small-Model Continuous Control
   Source: cs.AI (Artificial Intelligence)
   Link: https://arxiv.org/abs/2607.21626
   We study whether Group Relative Policy Optimization (GRPO) can fine-tune small language models for simulated quadrotor continuous-control tasks.
14. Effect of Graph Gluing on Consensus in Networked Multi-Agent Systems
   Source: cs.SY (Systems and Control)
   Link: https://arxiv.org/abs/2605.10558
   In this paper, the effects of graph gluing operations in networks of multi-agent systems and their impact on system performance are investigated.
15. Math Education Digital Shadows for Investigating Learning with GenAI: Mathematics Performance, Anxiety, and Confidence in LLMs
   Source: cs.SI (Social and Information Networks)
   Link: https://arxiv.org/abs/2604.27618
   Understanding the impact of large language models (LLMs) on mathematics education requires data on LLMs' mathematical performance and biases.
16. Comparing and Conceptualizing Data Protection Requirements Worldwide for Privacy Regulatory Compliance
   Source: cs.SE (Software Engineering)
   Link: https://arxiv.org/abs/2607.22270
   The growing digitalization of society has intensified the collection, processing, and sharing of personal data, increasingly moving across national borders and regulatory jurisdictions, prompting a proliferation of data protection frameworks worldwide.
17. Local Multimodal Music Alignment from Global Supervision
   Source: cs.SD (Sound)
   Link: https://arxiv.org/abs/2607.10023
   Understanding music requires understanding localized relationships across data modalities, e.g., how time in performance audio maps onto position in a score image.
18. Teachy Mini: Development and Preliminary Evaluation of a Knowledge-Based Generative Social Robot for Higher Education
   Source: cs.RO (Robotics)
   Link: https://arxiv.org/abs/2607.22345
   Generative social robots (GSRs) powered by large language models offer new possibilities for personalized tutoring in higher education, but also introduce risks related to misinformation, missing transparency, or reinforcing incorrect student responses.
19. Belobog: Move Language Fuzzing Framework For Real-World Smart Contracts
   Source: cs.PL (Programming Languages)
   Link: https://arxiv.org/abs/2512.02918
   Move is a resource-oriented programming language designed for secure and verifiable smart contract development and has been widely used in managing billions of digital assets in blockchains, such as Sui and Aptos.Move features a strong static type system and explicit resource semantics to enforce safety properties such as the prevention of data races, invalid asset transfers, and entry vulnerabilities.
20. PRISM: Evaluating POSIX Storage Systems for AI Research Workflows
   Source: cs.PF (Performance)
   Link: https://arxiv.org/abs/2607.21746
   The rapid advancement of AI research is driven by massive investments in GPU clusters, yet the critical role of storage systems in enabling efficient research workflows is often overlooked.
21. Genesis: An Empirical Platform for Studying Open-Ended Evolution Without Fitness Functions
   Source: cs.NE (Neural and Evolutionary Computing)
   Link: https://arxiv.org/abs/2607.21631
   Biological evolution sustains complex dynamics without any fitness function, yet virtually all evolutionary algorithms depend on one.
22. Not Birds of a Feather: Personality-Based Partner Selection in LLM Agents
   Source: cs.MA (Multiagent Systems)
   Link: https://arxiv.org/abs/2607.19785
   LLM-based agents increasingly operate in multi-agent ecosystems where a coordinating agent chooses which other agents to work with, and agents are increasingly given personalities through persona prompts.
23. Searching the Space of Feed-Forward Neural-Network Weight-Update Rules with Fixed Depth Symbolic Regression
   Source: cs.LG (Machine Learning)
   Link: https://arxiv.org/abs/2607.21855
   We investigate whether symbolic regression can discover explicit neural network weight-update rules that outperform standard hand-designed optimizers on small symbolic regression benchmarks.
24. SURE-RAG: Sufficiency and Uncertainty-Aware Evidence Verification for Selective Retrieval-Augmented Generation
   Source: cs.IR (Information Retrieval)
   Link: https://arxiv.org/abs/2605.03534
   Retrieval-augmented generation (RAG) grounds answers in retrieved passages, yet relevance does not guarantee sufficiency: a topical passage may still fail to justify the answer.
25. GPU-Accelerated ANNS: Quantized for Speed, Built for Change
   Source: cs.DB (Databases)
   Link: https://arxiv.org/abs/2601.07048
   Approximate nearest neighbor search (ANNS) is a core problem in machine learning and information retrieval applications.
26. Benchmarking the Safety of Large Language Models for Robotic Health Attendant Control
   Source: cs.CY (Computers and Society)
   Link: https://arxiv.org/abs/2604.26577
   Large language models (LLMs) are increasingly considered for deployment as the control component of robotic health attendants, yet their safety in this context remains poorly characterized.
27. CommandLM: Data driven behavior level descriptor for ego vehicles
   Source: cs.CV (Computer Vision and Pattern Recognition)
   Link: https://arxiv.org/abs/2607.22078
   As autonomous driving systems move toward real-world deployment, interpretable, behavior-level decision-making is essential for safety, trust, and regulation.

Sources in this brief: cs.AI (Artificial Intelligence); cs.AR (Hardware Architecture); cs.CC (Computational Complexity); cs.CE (Computational Engineering, Finance, and Science); cs.CL (Computation and Language); cs.CV (Computer Vision and Pattern Recognition); cs.CY (Computers and Society); cs.DB (Databases); cs.IR (Information Retrieval); cs.LG (Machine Learning); cs.MA (Multiagent Systems); cs.MS (Mathematical Software); cs.NE (Neural and Evolutionary Computing); cs.PF (Performance); cs.PL (Programming Languages); cs.RO (Robotics); cs.SD (Sound); cs.SE (Software Engineering); cs.SI (Social and Information Networks); cs.SY (Systems and Control).
Selected 27 of 227 available items for this weekly brief.