Good Papers

Showing papers from University of Sussex Show all papers

45%Niche pick
?Niche pickVote to see the score

Claims of AI emergence should be grounded in information decomposition

Christoph Riedl, Fernando Rosas

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

– ReadersNo votes yet
0/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 0 of 20 reviewers recommend it
lenient 0/5
medium 0/10
strict 0/5
91%Must read
?Must readVote to see the score

The Attacker in the Mirror: Breaking Self-Consistency in Safety via Anchored Bipolicy Self-Play

Anchored Bipolicy Self-Play uses frozen-base LoRA adapters to separate attacker and defender roles, preventing self-consistency collapse and improving safety with 100x greater parameter efficiency.

Gabriele La Malfa, Emanuele La Malfa, Saar Cohen, Jie Zhang and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
17/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 10/10
strict 2/5
76%Highly rated
?Highly ratedVote to see the score

From Density Matrices to Phase Transitions in Deep Learning: Spectral Early Warnings and Interpretability

A 2-datapoint reduced density matrix provides unified spectral early warnings of training phase transitions and interpretable eigenvectors across deep learning settings.

Max Hennick, Guillaume Corlouer

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

– ReadersNo votes yet
10/20 AI panelreviewers recommend it

Readers and the AI panel: vote on this paper to see what they said.

Only vote on papers you've read. Sign in with GitHub to vote.

AI panel: 10 of 20 reviewers recommend it
lenient 3/5
medium 6/10
strict 1/5