
CLEVER: A Curated Benchmark for Formally Verified Code Generation
Jul 9, 2025 · TL;DR: We introduce CLEVER, a hand-curated benchmark for verified code generation in Lean. It requires full formal specs and proofs. No few-shot method solves all …
We introduce CLEVER, the first curated benchmark for evaluating the generation of specifications and formally verified code in Lean. The benchmark comprises of 161 programming problems; …
Submissions | OpenReview
Jan 22, 2025 · Promoting openness in scientific communication and the peer-review process
STAIR: Improving Safety Alignment with Introspective Reasoning
May 1, 2025 · One common approach is training models to refuse unsafe queries, but this strategy can be vulnerable to clever prompts, often referred to as jailbreak attacks, which can …
EvoTest: Evolutionary Test-Time Learning for Self-Improving …
Sep 16, 2025 · A fundamental limitation of current AI agents is their inability to learn complex skills on the fly at test time, often behaving like “clever but clueless interns” in novel …
579 In this paper, we have proposed a novel counter- factual framework CLEVER for debiasing fact- checking models. Unlike existing works, CLEVER is augmentation-free and mitigates …
KnowTrace: Explicit Knowledge Tracing for Structured...
Sep 13, 2024 · TL;DR: We introduce a structured RAG paradigm (KnowTrace) that seamlessly integrates knowledge structuring and multi-step reasoning for improved MHQA performance.
Dual-Model Defense: Safeguarding Diffusion Models from …
Sep 27, 2024 · Membership inference and memorization is a key challenge with diffusion models. Mitigating such vulnerabilities is hence an important topic. The idea of using an ensemble of …
Measuring Mathematical Problem Solving With the MATH Dataset
Oct 18, 2021 · Abstract: Many intellectual endeavors require mathematical problem solving, but this skill remains beyond the capabilities of computers. To measure this ability in machine …
Do Histopathological Foundation Models Eliminate Batch Effects?
Oct 11, 2024 · Deep learning has led to remarkable advancements in computational histopathology, e.g., in diagnostics, biomarker prediction, and outcome prognosis. Yet, the …