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Reasoning Over Paragraph Effects in Situations
v1v2 (latest)

Reasoning Over Paragraph Effects in Situations

Conference on Empirical Methods in Natural Language Processing (EMNLP), 2019
16 August 2019
Kevin Lin
Oyvind Tafjord
Peter Clark
Matt Gardner
ArXiv (abs)PDFHTML

Papers citing "Reasoning Over Paragraph Effects in Situations"

50 / 89 papers shown
AceSearcher: Bootstrapping Reasoning and Search for LLMs via Reinforced Self-Play
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Yuchen Zhuang
Zihan Dong
Jonathan Wang
Yue Yu
Joyce C. Ho
Linjun Zhang
Haoyu Wang
W. Shi
Carl Yang
RALMReLMKELMLRM
189
7
0
29 Sep 2025
Natural Language Satisfiability: Exploring the Problem Distribution and Evaluating Transformer-based Language Models
Natural Language Satisfiability: Exploring the Problem Distribution and Evaluating Transformer-based Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL), 2025
Tharindu Madusanka
Ian Pratt-Hartmann
Riza Batista-Navarro
LRM
138
4
0
23 Aug 2025
AQuilt: Weaving Logic and Self-Inspection into Low-Cost, High-Relevance Data Synthesis for Specialist LLMs
AQuilt: Weaving Logic and Self-Inspection into Low-Cost, High-Relevance Data Synthesis for Specialist LLMs
Xiaopeng Ke
Hexuan Deng
Xuebo Liu
Jun Rao
Zhenxi Song
Jun-chen Yu
Min Zhang
SyDa
266
3
0
24 Jul 2025
Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMs
Leveraging Submodule Linearity Enhances Task Arithmetic Performance in LLMsInternational Conference on Learning Representations (ICLR), 2025
Rui Dai
Sile Hu
Xu Shen
Yonggang Zhang
Xinmei Tian
Jieping Ye
MoMe
367
9
0
15 Apr 2025
SuperMerge: An Approach For Gradient-Based Model Merging
SuperMerge: An Approach For Gradient-Based Model Merging
Haoyu Yang
Zheng Zhang
Saket Sathe
MoMe
425
0
0
17 Feb 2025
SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains
SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized DomainsNorth American Chapter of the Association for Computational Linguistics (NAACL), 2024
Ran Xu
Hui Liu
Jiapeng Liu
Zhenwei Dai
Yaochen Xie
...
Chen Luo
Yang Li
Joyce C. Ho
Carl Yang
Qi He
RALM
617
37
0
28 Jan 2025
A Little Human Data Goes A Long Way
A Little Human Data Goes A Long WayAnnual Meeting of the Association for Computational Linguistics (ACL), 2024
Dhananjay Ashok
Jonathan May
SyDa
645
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0
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What Matters for Model Merging at Scale?
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Prateek Yadav
Tu Vu
Jonathan Lai
Alexandra Chronopoulou
Manaal Faruqui
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Tsendsuren Munkhdalai
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301
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04 Oct 2024
SciDFM: A Large Language Model with Mixture-of-Experts for Science
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Liangtai Sun
Danyu Luo
Da Ma
Zihan Zhao
Baocai Chen
Zhennan Shen
Su Zhu
Lu Chen
Xin Chen
Kai Yu
MoE
206
6
0
27 Sep 2024
100 instances is all you need: predicting the success of a new LLM on
  unseen data by testing on a few instances
100 instances is all you need: predicting the success of a new LLM on unseen data by testing on a few instances
Lorenzo Pacchiardi
Lucy G. Cheke
José Hernández-Orallo
ALMLRMELM
309
21
0
05 Sep 2024
RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in
  LLMs
RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs
Yue Yu
Ming-Yu Liu
Zihan Liu
Wei Ping
Jiaxuan You
Chao Zhang
Mohammad Shoeybi
Bryan Catanzaro
ALMRALM
454
233
0
02 Jul 2024
Instruction Pre-Training: Language Models are Supervised Multitask
  Learners
Instruction Pre-Training: Language Models are Supervised Multitask Learners
Daixuan Cheng
Yuxian Gu
Shaohan Huang
Junyu Bi
Shiyu Huang
Furu Wei
SyDa
334
74
0
20 Jun 2024
Paraphrasing in Affirmative Terms Improves Negation Understanding
Paraphrasing in Affirmative Terms Improves Negation Understanding
MohammadHossein Rezaei
Eduardo Blanco
323
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0
11 Jun 2024
Localizing Task Information for Improved Model Merging and Compression
Localizing Task Information for Improved Model Merging and CompressionInternational Conference on Machine Learning (ICML), 2024
Ke Wang
Nikolaos Dimitriadis
Guillermo Ortiz-Jimenez
Franccois Fleuret
Pascal Frossard
MoMe
332
106
0
13 May 2024
Continual Learning of Large Language Models: A Comprehensive Survey
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Haizhou Shi
Zihao Xu
Hengyi Wang
Weiyi Qin
Wenyuan Wang
Yibin Wang
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Hao Wang
CLLKELMLRM
475
230
0
25 Apr 2024
Multi-Task Inference: Can Large Language Models Follow Multiple
  Instructions at Once?
Multi-Task Inference: Can Large Language Models Follow Multiple Instructions at Once?
Seunghyeok Hong
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Guijin Son
Seungone Kim
ELMLRM
494
31
0
18 Feb 2024
CFMatch: Aligning Automated Answer Equivalence Evaluation with Expert
  Judgments For Open-Domain Question Answering
CFMatch: Aligning Automated Answer Equivalence Evaluation with Expert Judgments For Open-Domain Question Answering
Zongxia Li
Ishani Mondal
Yijun Liang
Huy Nghiem
Jordan L. Boyd-Graber
ALMELM
306
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0
24 Jan 2024
ChatQA: Surpassing GPT-4 on Conversational QA and RAG
ChatQA: Surpassing GPT-4 on Conversational QA and RAG
Zihan Liu
Ming-Yu Liu
Rajarshi Roy
Peng Xu
Chankyu Lee
Mohammad Shoeybi
Bryan Catanzaro
ALMRALMAI4MH
669
100
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Merging by Matching Models in Task Parameter Subspaces
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MoMe
374
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Do Smaller Language Models Answer Contextualised Questions Through
  Memorisation Or Generalisation?
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Tim Hartill
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261
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Ana Marasović
170
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Towards LogiGLUE: A Brief Survey and A Benchmark for Analyzing Logical
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Man Luo
Shrinidhi Kumbhar
Ming shen
Mihir Parmar
Neeraj Varshney
Pratyay Banerjee
Somak Aditya
Chitta Baral
ReLMELMLRM
536
48
0
02 Oct 2023
Learning Deductive Reasoning from Synthetic Corpus based on Formal Logic
Learning Deductive Reasoning from Synthetic Corpus based on Formal LogicInternational Conference on Machine Learning (ICML), 2023
Terufumi Morishita
Gaku Morio
Atsuki Yamaguchi
Yasuhiro Sogawa
ReLMLRMAI4CEELM
321
44
0
11 Aug 2023
Teaching Smaller Language Models To Generalise To Unseen Compositional
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297
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Text Alignment Is An Efficient Unified Model for Massive NLP Tasks
Text Alignment Is An Efficient Unified Model for Massive NLP TasksNeural Information Processing Systems (NeurIPS), 2023
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Yichi Yang
Ruichen Li
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ALM
390
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Chain-of-Questions Training with Latent Answers for Robust Multistep
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Jesse Thomason
Robin Jia
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335
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Srijan Bansal
Semih Yavuz
Bo Pang
Meghana Moorthy Bhat
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455
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Teaching Probabilistic Logical Reasoning to Transformers
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Parisa Kordjamshidi
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Prompting with Pseudo-Code Instructions
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Mayank Mishra
Praveen Venkateswaran
Riyaz Ahmad Bhat
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415
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Pre-Training to Learn in Context
Pre-Training to Learn in ContextAnnual Meeting of the Association for Computational Linguistics (ACL), 2023
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Evaluating Open-Domain Question Answering in the Era of Large Language
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