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A dynamic coordination protocol for LLM teams cuts token use, runtime and coordination failures compared with static or hierarchical approaches, while maintaining or improving task accuracy across multiple tasks and base models.
n/a descriptive Full text arxiv
Improving the Efficiency of Language Agent Teams with Adaptive Task Graphs · Elizabeth Mieczkowski, Alexander Ku, Tiwalayo Eisape, Dilip Arumugam, John Matte... · May 07, 2026
A new foundation model for tabular data (Schema-1) learns tables natively and outperforms current tabular methods on prediction and imputation benchmarks; if its benchmark gains transfer to production datasets, it could materially reduce preprocessing overhead and accelerate adoption of AI across data-driven firms.
medium descriptive Full text arxiv
Data Language Models: A New Foundation Model Class for Tabular Data · Eda Erol, Giuliano Pezzoli, Ozer Cem Kelahmet · May 07, 2026
Static fairness rules can worsen long-term inequality while creating high short-term costs, but modest investment policies can erase disparities at low utility loss; the paper shows analytically that fair-seeming constraints may backfire over time and that dynamic interventions offer a cheaper path to equality.
medium theoretical Full text arxiv
Price of Fairness in Short-Term and Long-Term Algorithmic Selections · Shahin Jabbari, Chen Wang · May 07, 2026
Commercial incentives, concentrated compute and data access channelled generative AI toward opaque, frontier models, while open-weight and sovereign alternatives persisted but remained marginal due to resource and institutional constraints; targeted socio-technical programmes could reorient development toward transparency, moderation and sustainable business models.
n/a theoretical Full text arxiv
Pathways to AGI · Gordon Fletcher, Saomai Vu Khan · May 07, 2026
Users notice stylistic differences in AI text but won't pay extra for them: an incentivized experiment finds no link between perceived aesthetic quality and willingness to pay, suggesting aesthetic upgrades are unlikely to justify price premia in current LLM markets.
low quasi_experimental Full text arxiv
Artificial Aesthetics: The Implicit Economics of Valuing AI-Generated Text · Arbaaz Karim · May 07, 2026
A self‑hosted legal small language model matches frontier LLMs on contract extraction and slashes inference costs by up to 97%, reducing hallucinations that drive review burden.
medium descriptive Full text arxiv
A Few Good Clauses: Comparing LLMs vs Domain-Trained Small Language Models on Structured Contract Extraction · Nicole Lincoln, Nick Whitehouse, Jaron Mar, Rivindu Perera · May 07, 2026
China’s government‑guided funds materially speed firms’ digital and intelligent transformation, especially in high‑tech firms and those with strong internal controls; the funds work largely by loosening finance constraints and promoting knowledge spillovers.
medium quasi_experimental Summary openalex
Government-Guided Funds and Corporate Digital–Intelligent Transformation · Fangzheng Zhu, Yuexiang Lu · May 07, 2026
AI increases firm innovation only up to a point: beyond an adoption index of 2.948, innovation falls as firms' patents become more similar; strong internal absorptive capacity delays decline while concentrated industries hasten it.
medium correlational Summary openalex
The Inverted-U Relationship Between AI and Corporate Innovation Performance · Xu Fan, Benye Wang · May 07, 2026
Guideline-aware AI drafts halve the time novice describers need to produce audio descriptions and ease cognitive load, but poor-quality AI output offers little help; effectiveness depends on a content-specific quality threshold.
medium quasi_experimental Full text arxiv
Making AI Drafts Count: A Quality Threshold in Audio Description Workflows · Lana Do, Shasta Ihorn, Charity M. Pitcher-Cooper, Sanjay Mirani, Gio Jung, Hyunj... · May 06, 2026
Automation can lift GDP and consumption if gains are large and ownership is widespread; but when ownership is concentrated and vulnerable, privately chosen automation overexpands and shifts income to capital and high-skill workers, harming low-wealth households.
n/a theoretical Full text arxiv
The Demand Externality of Automation · Erhan Bayraktar · May 06, 2026
Constraint-aware scaffolding makes AI-generated services markedly more deployable and less brittle than generic code-generation workflows, by embedding production constraints via template retrieval and iterative clarification; this aligns AI-assisted prototyping closer to production engineering needs.
medium quasi_experimental Full text arxiv
Architectural Constraints Alignment in AI-assisted, Platform-based Service Development · Julius Irion, Moritz Leugers, Paul Hartwig, Simon Kling, Tachmyrat Annayev, Alex... · May 06, 2026
A curated drug-asset index dramatically improves LLM-powered competitive scouting: Gosset finds 3.2× more verified long-tail oncology assets per query than leading web-search models in a 10-target benchmark. Turning the same curated index into a callable tool lets other frontier models recover most of that advantage, implying search/data coverage — not model bells and whistles — is the main bottleneck.
medium descriptive Full text arxiv
Curated AI beats frontier LLMs at pharma asset discovery · Łukasz Kidziński, Kevin Thomas · May 06, 2026
A transformer trained on patent classification codes can forecast novel technological pairings years — sometimes decades — ahead by detecting collective shifts in how technologies are described, and it also improves representations for common patent analysis tasks.
medium correlational Full text arxiv
Anticipating Innovation Using Large Language Models · Enrico Maria Fenoaltea, Filippo Santoro, Giordano De Marzo, Segun Taofeek Aroyeh... · May 06, 2026
GenAI coding assistants deliver modest productivity gains—about a third of a standard deviation—mostly in controlled experiments, but they do not reliably boost learning or skill acquisition in educational settings.
medium review_meta Full text arxiv
A meta-analysis of the effect of generative AI on productivity and learning in programming · Sebastian Maier, Moritz Gunzenhäuser, Jonas Schweisthal, Manuel Schneider, Stefa... · May 06, 2026
AI that monitors pairs’ effort and gaze makes pair programming more effective: combined reactive prompts improve coordination and performance, and proactive, forecast-based support prevents breakdowns before they occur.
high quasi_experimental Full text arxiv
Cognitive Alignment Drives Attention: Modeling and Supporting Socially Shared Regulation in Pair Programming · Anahita Golrang, Kshitij Sharma · May 06, 2026
DAO-governed stacks could enable permissionless, community-owned AI-driven physical infrastructure by linking energy, sensing, compute and robots, but deployment risks — from security and centralization to incentive failures and legal exposure — mean scalable use will depend on continuously adaptive, value-sensitive governance.
n/a theoretical Full text arxiv
DAO-enabled decentralized physical AI: A new paradigm for human-machine collaboration · Mark C. Ballandies, Florian Spychiger, Uwe Serdült, Claudio J. Tessone · May 06, 2026
Chinese energy‑intensive listed firms that emphasize digital technologies make faster low‑carbon progress, largely by boosting R&D and cutting operating costs. The effect is strongest for large, non‑state firms and for firms in central and western regions.
medium correlational Full text openalex
The Impact of Digital Technology Integration on Low-Carbon Transformation in Energy-Intensive Enterprises: An Empirical Study Based on A-Share Listed Companies in Shanghai and Shenzhen · Zijing Liu · May 06, 2026
By 2025–early 2026, agentic and multimodal AI moved from demonstration to broad early adoption, with agentic coding tools beginning to automate end-to-end software workflows; U.S. policymakers have accelerated standards and procurement oversight but have not passed a single unified AI Act.
n/a commentary Full text openalex
Emerging AI Trends · Maikel Leon, Robert Plant · May 06, 2026
The AI boom reshapes, but does not uniformly strengthen, global market linkages: overall connectedness fell modestly after ChatGPT's launch, with AI stocks losing their initial role as net shock transmitters while the S&P 500 stayed the primary source of spillovers.
medium correlational Summary openalex
Artificial Intelligence and Financial Market Connectedness: Evidence from AI-Related Equities, Cryptocurrencies, and Global Assets · Shigeyuki Hamori · May 06, 2026
Decomposing AI recommendations into individually verifiable claims sharply raises clinician trust—trust rates jump from 27% to 66% and the effect is very large (d = 0.94). Traditional transparency tools produce only modest, dose‑response improvements.
high rct Full text arxiv
Atomic Fact-Checking Increases Clinician Trust in Large Language Model Recommendations for Oncology Decision Support: A Randomized Controlled Trial · Lisa C. Adams, Linus Marx, Erik Thiele Orberg, Keno Bressem, Sebastian Ziegelmay... · May 05, 2026
Optimizing models for agent-facing interpretability substantially boosts autonomous data‑science agents: evolved regressors both improve prediction quality and make models more 'simulatable' by LLMs, increasing ADS performance on the BLADE benchmark (Copilot CLI, Claude Code, Codex) by as much as 73%. Gains are demonstrated on tabular tasks using an LLM-graded interpretability metric and may not directly translate to human interpretability or broader real-world workflows.
medium descriptive Full text arxiv
Agentic-imodels: Evolving agentic interpretability tools via autoresearch · Chandan Singh, Yan Shuo Tan, Weijia Xu, Zelalem Gero, Weiwei Yang, Michel Galley... · May 05, 2026
U.S. workforce retraining largely restores wages but rarely shifts workers away from automation-prone jobs; employer-led apprenticeships show the biggest payoff. The WIOA system appears to support short-term wage recovery for vulnerable workers but is not structured to deliver large-scale cross-industry transitions away from routine, automation-exposed work.
medium correlational Full text arxiv
Did US Worker Retraining Reduce Participant Automation Exposure? · Julian Jacobs, Jordan Canedy · May 05, 2026
A large new benchmark of real-world file workspaces finds AI agents far from human-level performance: the best system scores 68.7% against a human 80.7%, with an average across agents of just 47.4%, exposing persistent weaknesses in cross-file reasoning and workspace-level decision-making.
n/a descriptive Full text arxiv
Workspace-Bench 1.0: Benchmarking AI Agents on Workspace Tasks with Large-Scale File Dependencies · Zirui Tang, Xuanhe Zhou, Yumou Liu, Linchun Li, Weizheng Wang, Hongzhang Huang, ... · May 05, 2026
Adoption of advanced, agent-like AI is linked to measurable productivity and growth gains but disproportionately benefits richer countries; developed economies capture markedly larger growth effects than emerging markets, risking reinforcement of existing global inequalities.
medium correlational Summary semantic_scholar
The Economic Value of Agentic AI: A Comparative Analysis of Its Impact on Growth and Business Productivity in Developed and Emerging Economies · Abayomi Titilola Olutimehin, Oluwadayo Mafolasere Olaniyi, Adegbenga Ismaila Ala... · Fetched May 05, 2026
Leading AI-data firms frame human expertise as a low-cost, extractable input to power models and pitch institutional ‘liberation’ to unlock talent for AI — a narrative that could reshape white-collar labour markets and the value of expertise.
low descriptive Full text arxiv
Cheap Expertise: Mapping and Challenging Industry Perspectives in the Expert Data Gig Economy · Robert Wolfe, Aayushi Dangol · May 05, 2026