From the 1 of 33 linked papers with an AI index.
33 papers
Scaling Evaluation-time Compute with Reasoning Models as Evaluators
Seungone Kim, Ian Wu, Jinu Lee +8
The paper studies how using larger, chain‑of‑thought reasoning language models as evaluators—by allocating more test‑time compute—can improve the accuracy of evaluating and reranki…
ImProver 2: Iteratively Self-Improving LMs for Neurosymbolic Proof Optimization
Riyaz Ahuja, Tate Rowney, Jeremy Avigad +1
Formal mathematics libraries are rapidly expanding, creating a growing need to refactor verified proofs for maintainability and to improve training data quality for neural provers.…
On the limits and opportunities of AI reviewers: Reviewing the reviews of Nature-family papers with 45 expert scientists
Seungone Kim, Dongkeun Yoon, Kiril Gashteovski +55
With the advancement of AI capabilities, AI reviewers are beginning to be deployed in scientific peer review, yet their capability and credibility remain in question: many scientis…
Reinforcing Human Behavior Simulation via Verbal Feedback
Weiwei Sun, Xuhui Zhou, Jiarui Liu +13
Humans learn social norms and behaviors from verbal feedback (e.g., a parent saying "that was rude" or a friend explaining "here's why that hurt"). Yet, learning from feedback for…
Soohak: A Mathematician-Curated Benchmark for Evaluating Research-level Math Capabilities of LLMs
Guijin Son, Seungone Kim, Catherine Arnett +73
Following the recent achievement of gold-medal performance on the IMO by frontier LLMs, the community is searching for the next meaningful and challenging target for measuring LLM…
Argument Reconstruction as Supervision for Critical Thinking in LLMs
Hyun Ryu, Gyouk Chu, Gregor Betz +3
To think critically about arguments, human learners are trained to identify, reconstruct, and evaluate arguments. Argument reconstruction is especially important because it makes a…