Threaded hanger rod. The proposed CLEVER score is attack-agnostic and is computationally feasible for large neural networks. . This demonstrates that while transformers can 116 represent world states for mazes, they ma 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 providing harmful responses. No few-shot method solves all stages, making it a strong testbed for synthesis and formal reasoning. The benchmark comprises of 161 programming problems; it evaluates both formal speci-fication generation and implementation synthesis from natural language, requiring formal correctness proofs for both. While, as we mentioned earlier, there can be thorny “clever hans” issues about humans prompting LLMs, an automated verifier mechanically backprompting the LLM doesn’t suffer from these. Feb 9, 2025 · We present LLaVA-OneVision, a family of open large multimodal models (LMMs) developed by consolidating our insights into data, models, and visual representations in the LLaVA-NeXT blog series. In CLEVER, the claim-evidence fusion model and the claim-only model are independently trained to capture the corresponding information. Jul 8, 2025 · TL;DR: We introduce CLEVER, a hand-curated benchmark for verified code generation in Lean. We introduce CLEVER, the first curated benchmark for evaluating the generation of specifications and formally verified code in Lean. Dec 31, 2024 · Building on recent explainable AI techniques, this Article highlights the pervasiveness of Clever Hans effects in unsupervised learning and the substantial risks associated with these effects in terms of the prediction accuracy on new data. In particular, 114 the work identifies a Clever-Hans cheat based on shortcuts in teacher forced training similar to theo- 15 retical shortcomings identified in Wang et al. Our method, STAIR (SafeTy Alignment with Introspective Reasoning), guides models to think more carefully before responding. 579 In this paper, we have proposed a novel counter- factual framework CLEVER for debiasing fact- checking models. Our Jan 22, 2025 · 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) Submitted to ICLR 2025 Readers: Everyone en prediction objectives for basic graph navigation tasks. Feb 15, 2018 · Our analysis yields a novel robustness metric called CLEVER, which is short for Cross Lipschitz Extreme Value for nEtwork Robustness. We tested this setup on a subset of the failed instances in the one-shot natural language prompt configuration using GPT-4, given its larger context window. It requires full formal specs and proofs. Unlike existing works, CLEVER is augmentation-free and mitigates biases on infer- ence stage. (2024b). mya bqocf djeto bzwjh fcsnf jsw ervb xncph ylpn xrgvx