ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2407.02514
  4. Cited By
LOGIC-LM++: Multi-Step Refinement for Symbolic Formulations

LOGIC-LM++: Multi-Step Refinement for Symbolic Formulations

22 June 2024
Shashank Kirtania
Priyanshu Gupta
Arjun Radhakirshna
    LRM
ArXivPDFHTML

Papers citing "LOGIC-LM++: Multi-Step Refinement for Symbolic Formulations"

5 / 5 papers shown
Title
PEIRCE: Unifying Material and Formal Reasoning via LLM-Driven Neuro-Symbolic Refinement
PEIRCE: Unifying Material and Formal Reasoning via LLM-Driven Neuro-Symbolic Refinement
Xin Quan
Marco Valentino
Danilo S. Carvalho
Dhairya Dalal
André Freitas
LRM
38
0
0
05 Apr 2025
Making LLMs Reason? The Intermediate Language Problem in Neurosymbolic Approaches
Making LLMs Reason? The Intermediate Language Problem in Neurosymbolic Approaches
Alexander Beiser
David Penz
LRM
51
0
0
24 Feb 2025
Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning
Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning
Hyun Ryu
Gyeongman Kim
Hyemin S. Lee
Eunho Yang
LRM
40
3
0
10 Oct 2024
DANA: Domain-Aware Neurosymbolic Agents for Consistency and Accuracy
DANA: Domain-Aware Neurosymbolic Agents for Consistency and Accuracy
Vinh Luong
Sang Dinh
Shruti Raghavan
William Nguyen
Zooey Nguyen
...
Kentaro Maegaito
Loc Nguyen
Thao Nguyen
Anh Hai Ha
Christopher Nguyen
26
0
0
27 Sep 2024
Large Language Models are Zero-Shot Reasoners
Large Language Models are Zero-Shot Reasoners
Takeshi Kojima
S. Gu
Machel Reid
Yutaka Matsuo
Yusuke Iwasawa
ReLM
LRM
322
4,077
0
24 May 2022
1