Maria Antoniak reposted
📣 New paper @nathumbehav.nature.com: A reporting checklist for large language models in behavioural science www.nature.com/articles/s41...
Who's Who of AI
Maria Antoniak
Assistant professor of CS, NLP and cultural analytics
NLP, cultural analytics. Assistant Professor of CS at University of Colorado Boulder. Books, bikes, games, art. https://maria-antoniak.github.io
What they're sharing
A reporting checklist for large language models in behavioural science - Nature Human Behaviour nature.com
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The AI Compass bambamramfan.github.io
Claude Fable is relentlessly proactive simonwillison.net
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Characterizing Narrative Content in Web-scale LLM Pretraining Data arxiv.org
AI Fiction in the Wild arxiv.org
AInterviewer: A Platform for Designing and Conducting AI-led Qualitative Interviews aclanthology.org
Creative Reading: Scaffolding Reading for Transformation arxiv.org
GitHub - davanstrien/uv-scripts-for-ai: Self-contained UV scripts for data & ML tasks — OCR, vision, audio & more — run one in a command, locally or on Hugging Face Jobs. Built for humans and agents. github.com
[2605.26097] Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay arxiv.org
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Accepted Main Conference Papers 2026.aclweb.org
Accepted Findings Papers 2026.aclweb.org
Accepted System Demonstrations Papers 2026.aclweb.org
Articles & links
not wrong! bambamramfan.github.io/ai-compass/
Maria Antoniak reposted
This is extremely unsettling. simonwillison.net/2026/Jun/11/...
Maria Antoniak reposted
2) Characterizing Narrative Content in Web-scale LLM Pretraining Data, by @teagrjohnson.bsky.social, @elliottash.bsky.social, @andrewpiper.bsky.social, @mariaa.bsky.social arxiv.org/abs/2606.19468 Why: annotation and analysis of narrative features across the pretraining data (…
AI Weekly's analysis
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- A new arXiv preprint introduces NarraBERT, a RoBERTa-based classifier, and applies it to 3 million passages from the 3-trillion-token Dolma corpus.
- The framework operationalizes three narrative elements, agency, setting, and events, across 11 interpretable dimensions, trained on 400 annotated passages.
- The authors report narrative qualities are unequally distributed across pretraining sources and topics in ways current curation practices do not measure.
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What are people really doing with chatbots? 👀 Turns out that a lot of them are writing/reading various kinds of fiction, and in particular, they're generating a ton of erotica! What does this mean for the future of reading? Paper: arxiv.org/abs/2606.22748 Web Explorer: ai-fict…
Maria Antoniak reposted
One of the things that AI now gets thrown into is qualitative interviews. I'm very lucky to work with real social scientists on the pros and cons of that. The first outcome of our @villumfonden.bsky.social grant with @hjalmarcarlsen.bsky.social is ACL'26 demo: aclanthology.org…
AI Weekly's analysis
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- AInterviewer uses a multi-agent framework combining structured survey question control with LLM conversational flexibility for qualitative research.
- The platform supports locally hosted language models to address reproducibility and data security concerns in academic research.
- A web-based interface covers the full qualitative research workflow: interview guide design, pilot testing, distribution, and data collection monitoring.
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Maria Antoniak reposted
How to create reading experiences that "go beyond information transmission and toward reader transformation.” Great paper by @blue-phia.bsky.social @lepidopterane.bsky.social @yijunliu.bsky.social Sarah Sterman @sh1m.bsky.social @maxkreminski.bsky.social arxiv.org/abs/2606.043…
AI Weekly's analysis
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- Researchers argue AI reading tools implicitly frame reading as information transmission, or 'reading to discard.'
- The paper maps reading augmentation onto two axes: transmission vs. transformation, and substituting vs. scaffolding.
- The concept of 'orienteering' argues readers benefit from moving through interpretive spaces rather than receiving direct answers.
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Maria Antoniak reposted
Got a digitised collection that needs OCR? uv-scripts is a set of single-file Python scripts that OCR a whole image dataset to markdown in one command — 20+ open VLMs to pick from, nothing to install but uv. github.com/davanstrien/...
AI Weekly's analysis
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- Each script is a self-contained Python file using PEP 723 inline dependency declarations, runnable with a single `uv run` command.
- Nine task categories are covered including OCR with 30+ models, audio transcription, vision detection, embeddings, and LLM inference.
- Scripts use standardized argument patterns so both humans and AI agents can run them locally or on Hugging Face Jobs GPU infrastructure.
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Maria Antoniak reposted
How much does a language model forget when finetuned on new tasks? We show both model size and optimization matter and forgetting can be nearly eliminated with self-generated replay! arxiv.org/abs/2605.26097 w/Martin Marek, Dongkyu Cho, Shikai Qiu, Rumi Chunara, and Pavel Izma…
Maria Antoniak reposted
We hope everyone is excited for ACL2026@San Diego. Feel free to take a look at the published papers below! Main: 2026.aclweb.org/program/acce... Findings: 2026.aclweb.org/program/find... Demos: 2026.aclweb.org/program/demo/ Industry track: 2026.aclweb.org/program/indu... #NLPr…
AI Weekly's analysis
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- ACL 2026's main conference reportedly accepted more than 2,400 papers from 12,145 submissions, an acceptance rate of about 19%.
- The 64th Annual Meeting of the Association for Computational Linguistics runs July 2-7, 2026 in San Diego with an 'Explainability of NLP Models' theme.
- The accepted-papers list is dominated by agentic systems, reasoning, multimodal learning, code, and safety and confidential-inference work.
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Maria Antoniak reposted
We hope everyone is excited for ACL2026@San Diego. Feel free to take a look at the published papers below! Main: 2026.aclweb.org/program/acce... Findings: 2026.aclweb.org/program/find... Demos: 2026.aclweb.org/program/demo/ Industry track: 2026.aclweb.org/program/indu... #NLPr…
AI Weekly's analysis
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- ACL 2026's Findings track has accepted 2,164 papers, released ahead of the July conference in San Diego.
- The 64th Annual Meeting runs July 2 to 7 at the Manchester Grand Hyatt, with in-person attendance capped at 3,500 per day.
- Topic mix skews to LLM capabilities, multimodal and vision-language systems, RAG, agents, and safety and bias work.
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Maria Antoniak reposted
We hope everyone is excited for ACL2026@San Diego. Feel free to take a look at the published papers below! Main: 2026.aclweb.org/program/acce... Findings: 2026.aclweb.org/program/find... Demos: 2026.aclweb.org/program/demo/ Industry track: 2026.aclweb.org/program/indu... #NLPr…
AI Weekly's analysis
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- ACL 2026's system demonstrations page lists accepted papers spanning explainability, multi-agent orchestration, and domain-specific LLM tooling.
- Several titles target LLM safety concerns including copyright leakage detection, membership inference, and psychosocial dialogue evaluation.
- The conference runs July 2 to 7, 2026 in San Diego, California, with demos covering biomedical, financial, and clinical NLP workflows.
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Their own posts
Recent commentary
I'm looking for 1-2 emergency reviewers for a #COLM2026 paper on LLMs and science. Paper looks like a nice read to me! Reply or message me if you might be able to write a review by end of week.
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