copy and paste this google map to your website or blog!
Press copy button and paste into your blog or website.
(Please switch to 'HTML' mode when posting into your blog. Examples: WordPress Example, Blogger Example)
CLEVER: A Curated Benchmark for Formally Verified Code Generation 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 strong testbed for synthesis and formal reasoning
Submissions - OpenReview Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answers Lorenzo Pacchiardi , Marko Tesic , Lucy G Cheke , Jose Hernandez-Orallo 27 Sept 2024 (modified: 05 Feb 2025)
Counterfactual Debiasing for Fact Verification - OpenReview 016 namely CLEVER, which is augmentation-free 017 and mitigates biases on the inference stage 018 Specifically, we train a claim-evidence fusion 019 model and a claim-only model independently 020 Then, we obtain the final prediction via sub-021 tracting output of the claim-only model from 022 output of the claim-evidence fusion model,
Clever: A Curated Benchmark for Formally Verified Code Generation 4CLEVER: Curated Lean Verified Code Generation Bench-mark microkernel However, writing formal specifications and correctness proofs for software systems can take tremen-dous effort — for example, the development of seL4 was reported to take 20+ person-years These costs are a key impediment to the broad deployment of ITP-based formal
STAIR: Improving Safety Alignment with Introspective Reasoning This is where safety alignment comes in 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 providing harmful responses
A survey on Concept-based Approaches For Model Improvement Explanations in terms of concepts enable detecting spurious correlations, inherent biases, or clever-hans With the advent of concept-based explanations, a range of concept representation methods and automatic concept discovery algorithms have been introduced
Thieves on Sesame Street! Model Extraction of BERT-based APIs Finally, we study two defense strategies against model extraction—membership classification and API watermarking—which while successful against some adversaries can also be circumvented by more clever ones