Zobrazeno 1 - 10
of 332
pro vyhledávání: '"GANESH, VIJAY"'
We introduce LLMStinger, a novel approach that leverages Large Language Models (LLMs) to automatically generate adversarial suffixes for jailbreak attacks. Unlike traditional methods, which require complex prompt engineering or white-box access, LLMS
Externí odkaz:
http://arxiv.org/abs/2411.08862
Due to the involvement of multiple intermediaries without trusted parties, lack of proper regulations, and a complicated supply chain, ad impression discrepancy affects online advertising. This issue causes up to $82 billion annual revenue loss for h
Externí odkaz:
http://arxiv.org/abs/2410.16141
We theoretically and empirically study the logical reasoning capabilities of LLMs in the context of the Boolean satisfiability (SAT) problem. First, we construct a decoder-only Transformer that can solve SAT using backtracking and deduction via Chain
Externí odkaz:
http://arxiv.org/abs/2410.07432
Blockchain integration in industries like online advertising is hindered by its connectivity limitations to off-chain data. These industries heavily rely on precise counting systems for collecting and analyzing off-chain data. This requires mechanism
Externí odkaz:
http://arxiv.org/abs/2409.11592
We present a new extended resolution clause learning (ERCL) algorithm, implemented as part of a conflict-driven clause-learning (CDCL) SAT solver, wherein new variables are dynamically introduced as definitions for {\it Dual Implication Points} (DIPs
Externí odkaz:
http://arxiv.org/abs/2406.14190
Reinforcement Learning with Human Feedback (RLHF) is considered a standard approach to fine-tuning Large Language Models (LLMs). However, such methods often face limitations such as unsound black-box reward models, difficulties in collecting human pr
Externí odkaz:
http://arxiv.org/abs/2405.16661
Restart policy is an important technique used in modern Conflict-Driven Clause Learning (CDCL) solvers, wherein some parts of the solver state are erased at certain intervals during the run of the solver. In most solvers, variable activities are pres
Externí odkaz:
http://arxiv.org/abs/2404.03753
Modern SMT solvers, such as Z3, offer user-controllable strategies, enabling users to tailor solving strategies for their unique set of instances, thus dramatically enhancing solver performance for their use case. However, this approach of strategy c
Externí odkaz:
http://arxiv.org/abs/2401.17159
This paper introduces AlphaMapleSAT, a novel Monte Carlo Tree Search (MCTS) based Cube-and-Conquer (CnC) SAT solving method aimed at efficiently solving challenging combinatorial problems. Despite the tremendous success of CnC solvers in solving a va
Externí odkaz:
http://arxiv.org/abs/2401.13770
One of the fundamental results in quantum foundations is the Kochen-Specker (KS) theorem, which states that any theory whose predictions agree with quantum mechanics must be contextual, i.e., a quantum observation cannot be understood as revealing a
Externí odkaz:
http://arxiv.org/abs/2306.13319