--- title: "Generative AI, organizations & the changing world." description: "Generative AI is changing how we work, build organizations and solve problems. In this blog, AI agents help us find and summarize research insights and discoveries and write about the possibilities they open up." url: "https://digitvibe.com/blog/" --- DigitVibe blog # Generative AI, organizations & the changing world. Generative AI is changing how we work, build organizations and solve problems. In this blog, AI agents help us find and summarize research insights and discoveries and write about the possibilities they open up. [Subscribe via RSS](https://digitvibe.com/blog/rss.xml) 1. ![Complete abstract from MT-Eval: A Multi-Turn Capabilities Evaluation Benchmark for Large Language Models.](https://digitvibe-blog.workspace-scripts.workers.dev/media/68707ea44f19e88563f12b08e68733ef0d0d195a42698204d0083e581ca7cf30.webp) Generative AI in organizations and societyNovember 12, 2026 ## Multi-turn AI chats expose weaknesses hidden by single-turn tests MT-Eval compares single- and multi-turn conversations and finds that models often lose ground as dialogue history grows. Read the article [Multi-turn AI chats expose weaknesses hidden by single-turn tests](https://digitvibe.com/blog/mt-eval-multi-turn-conversation-tests/) 2. ![Complete abstract from Is this the real life? Is this just fantasy? The Misleading Success of Simulating Social Interactions With LLMs.](https://digitvibe-blog.workspace-scripts.workers.dev/media/6c16cbe0de949d425fb9c4548fa5c96533e0522d92fea45a9a09fc81f76c494f.webp) AI and social simulationNovember 11, 2026 ## Is this the real life? Is this just fantasy? The Misleading Success of Simulating Social Interactions With LLMs Simulations with full access to every character’s goals look more successful than interactions where each agent has realistic private information. Read the article [Is this the real life? Is this just fantasy? The Misleading Success of Simulating Social Interactions With LLMs](https://digitvibe.com/blog/misleading-success-llm-social-simulations/) 3. ![Complete abstract from Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps.](https://digitvibe-blog.workspace-scripts.workers.dev/media/c7e78e5724c75954f9cd6519e1a27470dc00c98fcaeb39be9acea4422ee54781.webp) Generative AI reliabilityNovember 10, 2026 ## Can attention maps reveal language-model hallucinations? Lookback Lens uses model attention to flag answers that drift from supplied context, with tests across summarization and question answering. Read the article [Can attention maps reveal language-model hallucinations?](https://digitvibe.com/blog/lookback-lens-context-hallucinations/) 4. ![Complete abstract from Do LLMs Plan Like Human Writers? Comparing Journalist Coverage of Press Releases with LLMs.](https://digitvibe-blog.workspace-scripts.workers.dev/media/2a5ea16939f0655319349a722e08585441e0a953ca26da71bb94bcaa92770d2d.webp) Generative AI in organizations and societyNovember 9, 2026 ## LLMs suggest news angles, but lack human creativity A study of journalism planning finds that language models align more closely with reporters on story angles than on sources, while producing less creative suggestions. Read the article [LLMs suggest news angles, but lack human creativity](https://digitvibe.com/blog/llms-journalism-angle-creativity/) 5. ![Complete abstract from Large Language Models for Data Annotation and Synthesis: A Survey.](https://digitvibe-blog.workspace-scripts.workers.dev/media/72a7b72c30cc8d6ab59481974da679d9b5bac3e54f308912a518ae3b472e8714.webp) AI and data workNovember 8, 2026 ## LLMs Can Help Build Training Data, With Quality Checks A survey maps how language models can create labels and examples, how teams assess them, and where synthetic data can introduce new risks. Read the article [LLMs Can Help Build Training Data, With Quality Checks](https://digitvibe.com/blog/llms-data-annotation-quality-checks/) 6. ![ReviewCritique Table 1: corpus statistics comparing human-written and LLM-generated reviews, including accepted and rejected paper groups.](https://digitvibe-blog.workspace-scripts.workers.dev/media/1c7558d4792fd9682ba3d8ff142b1012ce44decd4db4fcfc3280435be95a76fd.webp) Science and researchNovember 7, 2026 ## LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing Experts marked more passages as deficient in AI-written peer reviews than in human reviews. Model feedback was less specific to individual papers. Read the article [LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing](https://digitvibe.com/blog/llm-review-critique-evidence/) 7. ![Complete abstract from The LLM Effect: Are Humans Truly Using LLMs, or Are They Being Influenced By Them Instead?.](https://digitvibe-blog.workspace-scripts.workers.dev/media/068055d6dce095837c23a4c54a013a23c642ba392b1f4b7d180b52082250980f.webp) AI and expert workNovember 6, 2026 ## The LLM Effect: Are Humans Truly Using LLMs, or Are They Being Influenced By Them Instead? A small study of policy analysts finds that LLM suggestions speed topic assignment while increasing alignment with the suggestions themselves. Read the article [The LLM Effect: Are Humans Truly Using LLMs, or Are They Being Influenced By Them Instead?](https://digitvibe.com/blog/llm-effect-expert-judgment-and-anchoring/) 8. ![Complete abstract from LitSearch: A Retrieval Benchmark for Scientific Literature Search.](https://digitvibe-blog.workspace-scripts.workers.dev/media/d7fb26976252f797dab3eb3033607a9488069c5f20d6b302b3cfee5a192b94e3.webp) Science and researchNovember 5, 2026 ## LitSearch: Benchmarking AI retrieval of scientific literature On 597 literature-search questions, an AI retriever outperformed keyword search. Using GPT-4o to reorder results improved retrieval further. Read the article [LitSearch: Benchmarking AI retrieval of scientific literature](https://digitvibe.com/blog/litsearch-scientific-retrieval/) 9. ![Complete abstract from Learn to Refuse: Making Large Language Models More Controllable and Reliable through Knowledge Scope Limitation and Refusal Mechanism.](https://digitvibe-blog.workspace-scripts.workers.dev/media/a0fe040c953a991d41c57e701df2fa38967fffff316dabd81e8ea76c143d6bd7.webp) Generative AI reliabilityNovember 4, 2026 ## When should an AI answer or refuse? Learn to Refuse pairs a structured knowledge base with a refusal mechanism and tests whether selective answers improve accuracy. Read the article [When should an AI answer or refuse?](https://digitvibe.com/blog/learn-to-refuse-language-models/) 10. ![Complete abstract from LawBench: Benchmarking Legal Knowledge of Large Language Models.](https://digitvibe-blog.workspace-scripts.workers.dev/media/98ed93f68e08f0f0fc89168cb3d75b8a543ca4bd1ba2cd7fb061bdc79b39ea1d.webp) AI governance and societyNovember 3, 2026 ## What legal knowledge can language models show? LawBench evaluates 21 systems across 20 Chinese legal tasks, revealing uneven skills and weak performance on many practical forms of legal reasoning. Read the article [What legal knowledge can language models show?](https://digitvibe.com/blog/lawbench-chinese-legal-knowledge/) --- DigitVibe. Index of public content: https://digitvibe.com/llms.txt