Debora Nozza
@deboranozza.bsky.social
Assistant Professor at Bocconi University in MilaNLP group • Working in #NLP, #HateSpeech and #Ethics • She/her • #ERCStG PERSONAE
Special thanks to my co-authors Emanuele Moscato, @tiancheng.bsky.social, @morlikow.bsky.social, @paul-rottger.bsky.social and the whole @milanlp.bsky.social lab for all the feedbacks!
October 31, 2025 at 5:05 PM
Special thanks to my co-authors Emanuele Moscato, @tiancheng.bsky.social, @morlikow.bsky.social, @paul-rottger.bsky.social and the whole @milanlp.bsky.social lab for all the feedbacks!
⚖️ Frameworks such as the EU’s Digital Services Act define legal boundaries, clarifying what constitutes illegal hate speech.
🤖 Our boundary model operationalizes these boundaries, reducing legal violations while minimally affecting overall user welfare measured by user-level performance
🤖 Our boundary model operationalizes these boundaries, reducing legal violations while minimally affecting overall user welfare measured by user-level performance
October 31, 2025 at 5:05 PM
⚖️ Frameworks such as the EU’s Digital Services Act define legal boundaries, clarifying what constitutes illegal hate speech.
🤖 Our boundary model operationalizes these boundaries, reducing legal violations while minimally affecting overall user welfare measured by user-level performance
🤖 Our boundary model operationalizes these boundaries, reducing legal violations while minimally affecting overall user welfare measured by user-level performance
Reposted by Debora Nozza
🗓️ Nov 5 – Main Conference Posters
Personalization up to a Point
🧠 In the context of content moderation, we show that fully personalized models can perpetuate hate speech, and propose a policy-based method to impose legal boundaries.
📍 Hall C | 11:00–12:30
Personalization up to a Point
🧠 In the context of content moderation, we show that fully personalized models can perpetuate hate speech, and propose a policy-based method to impose legal boundaries.
📍 Hall C | 11:00–12:30
October 31, 2025 at 2:05 PM
🗓️ Nov 5 – Main Conference Posters
Personalization up to a Point
🧠 In the context of content moderation, we show that fully personalized models can perpetuate hate speech, and propose a policy-based method to impose legal boundaries.
📍 Hall C | 11:00–12:30
Personalization up to a Point
🧠 In the context of content moderation, we show that fully personalized models can perpetuate hate speech, and propose a policy-based method to impose legal boundaries.
📍 Hall C | 11:00–12:30
Reposted by Debora Nozza
🗓️ Nov 5 – Main Conference Posters
📘 Biased Tales
A dataset of 5k short LLM bedtime stories generated across sociocultural axes with an evaluation taxonomy for character-centric attributes and context-centric attributes.
📍 Hall C | 11:00–12:30
📘 Biased Tales
A dataset of 5k short LLM bedtime stories generated across sociocultural axes with an evaluation taxonomy for character-centric attributes and context-centric attributes.
📍 Hall C | 11:00–12:30
October 31, 2025 at 2:05 PM
🗓️ Nov 5 – Main Conference Posters
📘 Biased Tales
A dataset of 5k short LLM bedtime stories generated across sociocultural axes with an evaluation taxonomy for character-centric attributes and context-centric attributes.
📍 Hall C | 11:00–12:30
📘 Biased Tales
A dataset of 5k short LLM bedtime stories generated across sociocultural axes with an evaluation taxonomy for character-centric attributes and context-centric attributes.
📍 Hall C | 11:00–12:30
Reposted by Debora Nozza
🗓️ Nov 5 - Demo
Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification
🧩 Co-DETECT – an iterative, human-LLM collaboration framework for surfacing edge cases and refining annotation codebooks in text classification.
📍 Demo Session 2 – Hall C3 | 14:30–16:00
Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification
🧩 Co-DETECT – an iterative, human-LLM collaboration framework for surfacing edge cases and refining annotation codebooks in text classification.
📍 Demo Session 2 – Hall C3 | 14:30–16:00
October 31, 2025 at 2:06 PM
🗓️ Nov 5 - Demo
Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification
🧩 Co-DETECT – an iterative, human-LLM collaboration framework for surfacing edge cases and refining annotation codebooks in text classification.
📍 Demo Session 2 – Hall C3 | 14:30–16:00
Co-DETECT: Collaborative Discovery of Edge Cases in Text Classification
🧩 Co-DETECT – an iterative, human-LLM collaboration framework for surfacing edge cases and refining annotation codebooks in text classification.
📍 Demo Session 2 – Hall C3 | 14:30–16:00
Reposted by Debora Nozza
🗓️ Nov 6 – Findings Posters
The “r” in “woman” stands for rights.
💬 We propose a taxonomy of social dynamics in implicit misogyny (EN,IT), auditing 9 LLMs — and they consistently fail. The more social knowledge a message requires, the worse they perform.
📍 Hall C | 12:30–13:30
The “r” in “woman” stands for rights.
💬 We propose a taxonomy of social dynamics in implicit misogyny (EN,IT), auditing 9 LLMs — and they consistently fail. The more social knowledge a message requires, the worse they perform.
📍 Hall C | 12:30–13:30
October 31, 2025 at 2:06 PM
🗓️ Nov 6 – Findings Posters
The “r” in “woman” stands for rights.
💬 We propose a taxonomy of social dynamics in implicit misogyny (EN,IT), auditing 9 LLMs — and they consistently fail. The more social knowledge a message requires, the worse they perform.
📍 Hall C | 12:30–13:30
The “r” in “woman” stands for rights.
💬 We propose a taxonomy of social dynamics in implicit misogyny (EN,IT), auditing 9 LLMs — and they consistently fail. The more social knowledge a message requires, the worse they perform.
📍 Hall C | 12:30–13:30
Reposted by Debora Nozza
🗓️ Nov 7 – Main Conference Posters
Principled Personas: Defining and Measuring the Intended Effects of Persona Prompting on Task Performance
🧍 Discussing different applications for LLM persona prompting, and how to measure their success.
📍 Hall C | 10:30–12:00
Principled Personas: Defining and Measuring the Intended Effects of Persona Prompting on Task Performance
🧍 Discussing different applications for LLM persona prompting, and how to measure their success.
📍 Hall C | 10:30–12:00
October 31, 2025 at 2:06 PM
🗓️ Nov 7 – Main Conference Posters
Principled Personas: Defining and Measuring the Intended Effects of Persona Prompting on Task Performance
🧍 Discussing different applications for LLM persona prompting, and how to measure their success.
📍 Hall C | 10:30–12:00
Principled Personas: Defining and Measuring the Intended Effects of Persona Prompting on Task Performance
🧍 Discussing different applications for LLM persona prompting, and how to measure their success.
📍 Hall C | 10:30–12:00
Reposted by Debora Nozza
🗓️ Nov 7 – Main Conference Posters
TrojanStego: Your Language Model Can Secretly Be a Steganographic Privacy-Leaking Agent
🔒 LLMs can be fine-tuned to leak secrets via token-based steganography!
📍 Hall C | 10:30–12:00
TrojanStego: Your Language Model Can Secretly Be a Steganographic Privacy-Leaking Agent
🔒 LLMs can be fine-tuned to leak secrets via token-based steganography!
📍 Hall C | 10:30–12:00
October 31, 2025 at 2:06 PM
🗓️ Nov 7 – Main Conference Posters
TrojanStego: Your Language Model Can Secretly Be a Steganographic Privacy-Leaking Agent
🔒 LLMs can be fine-tuned to leak secrets via token-based steganography!
📍 Hall C | 10:30–12:00
TrojanStego: Your Language Model Can Secretly Be a Steganographic Privacy-Leaking Agent
🔒 LLMs can be fine-tuned to leak secrets via token-based steganography!
📍 Hall C | 10:30–12:00
Reposted by Debora Nozza
🗓️ Nov 8 – WiNLP Workshops
No for Some, Yes for Others
🤖 We investigate how sociodemographic persona prompts affect false refusal behaviors in LLMs. Model and task type are the dominant factors driving these refusals.
No for Some, Yes for Others
🤖 We investigate how sociodemographic persona prompts affect false refusal behaviors in LLMs. Model and task type are the dominant factors driving these refusals.
October 31, 2025 at 2:06 PM
🗓️ Nov 8 – WiNLP Workshops
No for Some, Yes for Others
🤖 We investigate how sociodemographic persona prompts affect false refusal behaviors in LLMs. Model and task type are the dominant factors driving these refusals.
No for Some, Yes for Others
🤖 We investigate how sociodemographic persona prompts affect false refusal behaviors in LLMs. Model and task type are the dominant factors driving these refusals.
Reposted by Debora Nozza
🗓️ Nov 8 – NLPerspectives Workshops
Balancing Quality and Variation
🧮 For datasets to represent diverse opinions, they must preserve variation while filtering out spam. We evaluate annotator filtering heuristics and show how they often remove genuine variation.
Balancing Quality and Variation
🧮 For datasets to represent diverse opinions, they must preserve variation while filtering out spam. We evaluate annotator filtering heuristics and show how they often remove genuine variation.
October 31, 2025 at 2:07 PM
🗓️ Nov 8 – NLPerspectives Workshops
Balancing Quality and Variation
🧮 For datasets to represent diverse opinions, they must preserve variation while filtering out spam. We evaluate annotator filtering heuristics and show how they often remove genuine variation.
Balancing Quality and Variation
🧮 For datasets to represent diverse opinions, they must preserve variation while filtering out spam. We evaluate annotator filtering heuristics and show how they often remove genuine variation.
Reposted by Debora Nozza
🗓️ Nov 8 – BabyLM Workshop
Teacher Demonstrations in a BabyLM's Zone of Proximal Development for Contingent Multi-Turn Interaction
👶 ContingentChat, a Teacher–Student framework that benchmarks and improves multi-turn contingency in a BabyLM trained on 100M words.
Teacher Demonstrations in a BabyLM's Zone of Proximal Development for Contingent Multi-Turn Interaction
👶 ContingentChat, a Teacher–Student framework that benchmarks and improves multi-turn contingency in a BabyLM trained on 100M words.
October 31, 2025 at 2:07 PM
🗓️ Nov 8 – BabyLM Workshop
Teacher Demonstrations in a BabyLM's Zone of Proximal Development for Contingent Multi-Turn Interaction
👶 ContingentChat, a Teacher–Student framework that benchmarks and improves multi-turn contingency in a BabyLM trained on 100M words.
Teacher Demonstrations in a BabyLM's Zone of Proximal Development for Contingent Multi-Turn Interaction
👶 ContingentChat, a Teacher–Student framework that benchmarks and improves multi-turn contingency in a BabyLM trained on 100M words.
Reposted by Debora Nozza
🗓️ Nov 8 – STARSEM Workshop
Generalizability of Media Frames: Corpus Creation and Analysis Across Countries
📰 We investigate how well media frames generalize across different media landscapes. The 15 MFC frames remain broadly applicable, with minor revisions of the guidelines.
Generalizability of Media Frames: Corpus Creation and Analysis Across Countries
📰 We investigate how well media frames generalize across different media landscapes. The 15 MFC frames remain broadly applicable, with minor revisions of the guidelines.
October 31, 2025 at 2:07 PM
🗓️ Nov 8 – STARSEM Workshop
Generalizability of Media Frames: Corpus Creation and Analysis Across Countries
📰 We investigate how well media frames generalize across different media landscapes. The 15 MFC frames remain broadly applicable, with minor revisions of the guidelines.
Generalizability of Media Frames: Corpus Creation and Analysis Across Countries
📰 We investigate how well media frames generalize across different media landscapes. The 15 MFC frames remain broadly applicable, with minor revisions of the guidelines.
Reposted by Debora Nozza
🗓️ Nov 6 – Oral Presentation (TACL)
IssueBench: Millions of Realistic Prompts for Measuring Issue Bias in LLM Writing Assistance
⚖️ A foundation for measuring LLM political bias in realistic user conversations.
📍 A303 | 10:30–12:00
IssueBench: Millions of Realistic Prompts for Measuring Issue Bias in LLM Writing Assistance
⚖️ A foundation for measuring LLM political bias in realistic user conversations.
📍 A303 | 10:30–12:00
October 31, 2025 at 2:07 PM
🗓️ Nov 6 – Oral Presentation (TACL)
IssueBench: Millions of Realistic Prompts for Measuring Issue Bias in LLM Writing Assistance
⚖️ A foundation for measuring LLM political bias in realistic user conversations.
📍 A303 | 10:30–12:00
IssueBench: Millions of Realistic Prompts for Measuring Issue Bias in LLM Writing Assistance
⚖️ A foundation for measuring LLM political bias in realistic user conversations.
📍 A303 | 10:30–12:00