From the 1 of 17 linked papers with an AI index.
17 papers
PiCSAR: Probabilistic Confidence Selection And Ranking for Reasoning Chains
Joshua Ong Jun Leang, Zheng Zhao, Aryo Pradipta Gema +7
The paper proposes PiCSAR, a training-free scoring method that uses the joint log-likelihood of reasoning steps and final answer to select the most reliable reasoning chain from mu…
Pythagoras-Prover: Advancing Efficient Formal Proving via Augmented Lean Formalisation
Joshua Ong Jun Leang, Zheng Zhao, Mihaela CÄtÄlina Stoian +5
Modern Lean theorem provers achieve strong performance only with substantial training and inference compute, driven in part by scarce verified proof data and the long reasoning tra…
Debiasing Without Protected Attributes: Latent Concept Erasure from Textual Profiles
Shun Shao, Zheng Zhao, Anna Korhonen +2
Most fairness research in NLP assumes direct access to protected attributes such as gender, race, or nationality. In practice, however, such information is often unavailable due to…
Can VLMs Predict Future States? Bootstrapping World Models from Inverse Dynamics
Yifu Qiu, Yftah Ziser, Anna Korhonen +2
Can unified vision-language models (VLMs) perform forward dynamics prediction (FDP), i.e., predicting the future state (in image form) given the previous observation and an action…
Old Habits Die Hard: How Conversational History Geometrically Traps LLMs
Adi Simhi, Fazl Barez, Martin Tutek +2
How does the conversational past of large language models (LLMs) influence their future performance? Recent work suggests that LLMs are affected by their conversational history in…
MoRFI: Monotonic Sparse Autoencoder Feature Identification
Dimitris Dimakopoulos, Shay B. Cohen, Ioannis Konstas
Large language models (LLMs) acquire most of their factual knowledge during the pre-training stage, through next token prediction. Subsequent stages of post-training often introduc…