
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 stages, making it a …
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; it evaluates …
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 trick the AI into …
EvoTest: Evolutionary Test-Time Learning for Self-Improving Agentic ...
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 environments. This …
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 biases on infer- …
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 Membership ...
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 model is …
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 learning models, …
Do Histopathological Foundation Models Eliminate Batch Effects? A ...
Oct 11, 2024 · Deep learning has led to remarkable advancements in computational histopathology, e.g., in diagnostics, biomarker prediction, and outcome prognosis. Yet, the lack of annotated data …