Chain-of-Thought Reasoning

ICML 2024arXiv:2305.14325

#2

Improving Factuality and Reasoning in Language Models through Multiagent Debate

Yilun Du, Shuang Li, Antonio Torralba et al.

multiagent debatelanguage model reasoningmathematical reasoningstrategic reasoning+4

1,274

AAAI 2024arXiv:2308.09687

#3

Graph of Thoughts: Solving Elaborate Problems with Large Language Models

Maciej Besta, Nils Blach, Ales Kubicek et al.

graph of thoughtslarge language modelsprompting capabilitiesthought transformations+4

1,116

CVPR 2024arXiv:2308.00692

#4

LISA: Reasoning Segmentation via Large Language Model

Xin Lai, Zhuotao Tian, Yukang Chen et al.

742

ICLR 2024arXiv:2310.01798

#5

Large Language Models Cannot Self-Correct Reasoning Yet

Jie Huang, Xinyun Chen, Swaroop Mishra et al.

738

NEURIPS 2025arXiv:2504.13837

#6

Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model?

Yang Yue, Zhiqi Chen, Rui Lu et al.

reinforcement learning with verifiable rewardsreasoning capacitylarge language modelsmathematics tasks+4

540

ICLR 2025arXiv:2410.05229

#7

GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

Iman Mirzadeh, Keivan Alizadeh-Vahid, Hooman Shahrokhi et al.

436

ICLR 2024arXiv:2310.01061

#8

Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning

Linhao Luo, Yuan-Fang Li, Reza Haffari et al.

415

ICLR 2025arXiv:2305.00050

#9

Causal Reasoning and Large Language Models: Opening a New Frontier for Causality

Chenhao Tan, Robert Ness, Amit Sharma et al.

causal reasoninglarge language modelscausal discoverycounterfactual reasoning+3

403

COLM 2025arXiv:2502.03387

#10

LIMO: Less is More for Reasoning

Yixin Ye, Zhen Huang, Yang Xiao et al.

Large language modelsMathematical reasoningData efficiencySupervised fine-tuning+2

383

ICCV 2025arXiv:2411.10440

#11

LLaVA-CoT: Let Vision Language Models Reason Step-by-Step

Guowei Xu, Peng Jin, ZiangWu ZiangWu et al.

vision-language modelschain-of-thought reasoningvisual question answeringmultimodal reasoning benchmarks+3

360

COLM 2025arXiv:2412.06769

#12

Training Large Language Models to Reason in a Continuous Latent Space

Shibo Hao, Sainbayar Sukhbaatar, DiJia Su et al.

chain of thoughtreasoning

357

COLM 2025arXiv:2503.01307

#13

Cognitive Behaviors that Enable Self-Improving Reasoners, or, Four Habits of Highly Effective STaRs

Kanishk Gandhi, Ayush K Chakravarthy, Anikait Singh et al.

ReasoningRLself-improvementbacktracking+3

318

ICML 2024arXiv:2309.17179

#14

AlphaZero-Like Tree-Search can Guide Large Language Model Decoding and Training

Ziyu Wan, Xidong Feng, Muning Wen et al.

tree-search algorithmslarge language modelsmulti-step reasoningvalue function learning+4

304

NEURIPS 2025arXiv:2506.06941

#15

The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity

Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh vahid et al.

large reasoning modelsreasoning capabilitiesproblem complexityscaling properties+4

277

ICCV 2025arXiv:2503.10615

#16

R1-Onevision: Advancing Generalized Multimodal Reasoning through Cross-Modal Formalization

yi yang, Xiaoxuan He, Hongkun Pan et al.

265

NEURIPS 2025arXiv:2503.21776

#17

Video-R1: Reinforcing Video Reasoning in MLLMs

Kaituo Feng, Kaixiong Gong, Bohao Li et al.

rule-based reinforcement learningmultimodal large language modelsvideo reasoningtemporal modeling+3

257

ICLR 2025arXiv:2409.12183

#18

To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoning

Zayne Sprague, Fangcong Yin, Juan Rodriguez et al.

chain-of-thought promptingsymbolic reasoningmathematical reasoninglarge language models+3

250

COLM 2025arXiv:2503.04697

#19

L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning

Pranjal Aggarwal, Sean Welleck

reasoning llmscontrollabilitytest-time comptue

250

CVPR 2025arXiv:2503.22020

#20

CoT-VLA: Visual Chain-of-Thought Reasoning for Vision-Language-Action Models

Qingqing Zhao, Yao Lu, Moo Jin Kim et al.

245

ICCV 2025arXiv:2503.12937

#21

R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization

Jingyi Zhang, Jiaxing Huang, Huanjin Yao et al.

220

ICLR 2024arXiv:2401.04398

#22

Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding

Zilong Wang, Hao Zhang, Chun-Liang Li et al.

209

ICLR 2024arXiv:2307.07697

#23

Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph

Jiashuo Sun, Chengjin Xu, Lumingyuan Tang et al.

198

CVPR 2024arXiv:2312.02228

#24

PixelLM: Pixel Reasoning with Large Multimodal Model

Zhongwei Ren, Zhicheng Huang, Yunchao Wei et al.

197

ICLR 2024arXiv:2310.06117

#25

Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models

Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen et al.

190

ICLR 2025arXiv:2404.02078

#26

Advancing LLM Reasoning Generalists with Preference Trees

Lifan Yuan, Ganqu Cui, Hanbin Wang et al.

large language modelsreasoning taskspreference learningalignment dataset+4

183

NEURIPS 2025arXiv:2504.08837

#27

VL-Rethinker: Incentivizing Self-Reflection of Vision-Language Models with Reinforcement Learning

Haozhe Wang, Chao Qu, Zuming Huang et al.

vision-language modelsreinforcement learningslow-thinking systemsmultimodal reasoning+4

183

ICLR 2024arXiv:2308.00436

#28

SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning

Ning Miao, Yee Whye Teh, Tom Rainforth

179

NEURIPS 2025arXiv:2502.04463

#29

Training Language Models to Reason Efficiently

Daman Arora, Andrea Zanette

178

ICLR 2024arXiv:2310.04560

#30

Talk like a Graph: Encoding Graphs for Large Language Models

Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi

174

CVPR 2024arXiv:2311.17076

#31

Compositional Chain-of-Thought Prompting for Large Multimodal Models

Chancharik Mitra, Brandon Huang, Trevor Darrell et al.

171

ICLR 2024arXiv:2302.02676

#32

Chain of Hindsight aligns Language Models with Feedback

Hao Liu, Carmelo Sferrazza, Pieter Abbeel

158

NEURIPS 2025arXiv:2502.05171

#33

Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach

Jonas Geiping, Sean McLeish, Neel Jain et al.

latent reasoningtest-time compute scalingrecurrent depth modelslanguage model architecture+4

158

ICLR 2024arXiv:2309.05660

#34

Hypothesis Search: Inductive Reasoning with Language Models

Ruocheng Wang, Eric Zelikman, Gabriel Poesia et al.

154

ICLR 2024arXiv:2305.13269

#35

Chain-of-Knowledge: Grounding Large Language Models via Dynamic Knowledge Adapting over Heterogeneous Sources

Xingxuan Li, Ruochen Zhao, Yew Ken Chia et al.

151

ICML 2024arXiv:2501.03230

#36

Video-of-Thought: Step-by-Step Video Reasoning from Perception to Cognition

Hao Fei, Shengqiong Wu, Wei Ji et al.

video understandingmultimodal large language modelsspatial-temporal scene graphsvideo question answering+4

146

ICLR 2024arXiv:2310.16049

#37

MuSR: Testing the Limits of Chain-of-thought with Multistep Soft Reasoning

Zayne Sprague, Xi Ye, Kaj Bostrom et al.

144

ICLR 2025arXiv:2309.14402

#38

Physics of Language Models: Part 3.2, Knowledge Manipulation

Zeyuan Allen-Zhu, Yuanzhi Li

143

ICLR 2024arXiv:2310.01714

#39

Large Language Models as Analogical Reasoners

Michihiro Yasunaga, Xinyun Chen, Yujia Li et al.

137

ICML 2024arXiv:2312.04474

#40

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Chengshu Li, Jacky Liang, Andy Zeng et al.

language model reasoningcode-driven reasoningpseudocode generationcode emulation+4

135

ICML 2025arXiv:2501.07542

#41

Imagine While Reasoning in Space: Multimodal Visualization-of-Thought

Chengzu Li, Wenshan Wu, Huanyu Zhang et al.

131

ICLR 2025arXiv:2408.06195

#42

Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solver

Zhenting Qi, Mingyuan MA, Jiahang Xu et al.

self-play reasoningmonte carlo tree searchmutual generation-discriminationsmall language models+3

129

ICLR 2024arXiv:2310.03094

#43

Large Language Model Cascades with Mixture of Thought Representations for Cost-Efficient Reasoning

Murong Yue, Jie Zhao, Min Zhang et al.

129

ICLR 2024arXiv:2312.13558

#44

The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction

Pratyusha Sharma, Jordan Ash, Dipendra Kumar Misra

118

ECCV 2024arXiv:2312.03661

#45

Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving

Ming Nie, Renyuan Peng, Chunwei Wang et al.

autonomous drivingvision-language modelsinterpretable reasoningchain-based reasoning+4

115

AAAI 2025arXiv:2403.14520

#46

Cobra: Extending Mamba to Multi-Modal Large Language Model for Efficient Inference

Han Zhao, Min Zhang, Wei Zhao et al.

multimodal large language modelslinear computational complexitymamba language modelmodal fusion schemes+4

110

ICLR 2024arXiv:2310.08559

#47

Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement

Linlu Qiu, Liwei Jiang, Ximing Lu et al.

110

ICLR 2025arXiv:2402.08115

#48

On the self-verification limitations of large language models on reasoning and planning tasks

Kaya Stechly, Karthik Valmeekam, Subbarao Kambhampati

self-verification limitationsiterative promptingreasoning tasksplanning tasks+3

109

NEURIPS 2025arXiv:2412.18319

#49

Mulberry: Empowering MLLM with o1-like Reasoning and Reflection via Collective Monte Carlo Tree Search

Huanjin Yao, Jiaxing Huang, Wenhao Wu et al.

collective monte carlo tree searchmultimodal large language modelsreasoning path searchstep-by-step reasoning+4

106

NEURIPS 2025arXiv:2505.24864

#50

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Mingjie Liu, Shizhe Diao, Ximing Lu et al.

reinforcement learningreasoning capabilitieskl divergence controlreference policy resetting+4

104

NEURIPS 2025arXiv:2502.18080

#51

Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning

Wenkai Yang, Shuming Ma, Yankai Lin et al.

test-time computechain of thoughtmathematical reasoningreasoning performance+3

103

ICML 2024arXiv:2402.10963

#52

GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements

Alexander Havrilla, Sharath Chandra Raparthy, Christoforos Nalmpantis et al.

process-based reward modelingreasoning refinementstepwise optimal reward modelssynthetic data generation+3

102

ICLR 2025arXiv:2407.20311

#53

Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process

Tian Ye, Zicheng Xu, Yuanzhi Li et al.

mathematical reasoninglanguage model interpretabilityhidden reasoning processgrade-school math+4

100

NEURIPS 2025arXiv:2505.00703

#54

T2I-R1: Reinforcing Image Generation with Collaborative Semantic-level and Token-level CoT

Dongzhi JIANG, Ziyu Guo, Renrui Zhang et al.

chain-of-thought reasoningtext-to-image generationreinforcement learningsemantic-level planning+3

100

ICML 2024arXiv:2308.10379

#55

Algorithm of Thoughts: Enhancing Exploration of Ideas in Large Language Models

Bilgehan Sel, Ahmad Al-Tawaha, Vanshaj Khattar et al.

algorithmic reasoning pathwaysin-context learninglarge language modelsreasoning capacities+4

99

CVPR 2025arXiv:2411.14432

#56

Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models

Yuhao Dong, Zuyan Liu, Hai-Long Sun et al.

96

ICML 2025arXiv:2410.21333

#57

Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse

Ryan Liu, Jiayi Geng, Addison J. Wu et al.

95

ICLR 2024arXiv:2309.16298

#58

At Which Training Stage Does Code Data Help LLMs Reasoning?

ma yingwei, Yue Liu, Yue Yu et al.

95

ICML 2025arXiv:2502.09621

#59

MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency

Dongzhi Jiang, Renrui Zhang, Ziyu Guo et al.

94

ICLR 2024arXiv:2401.10480

#60

Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning

Yiwei Li, Peiwen Yuan, Shaoxiong Feng et al.

90

NEURIPS 2025arXiv:2506.01347

#61

The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning

Xinyu Zhu, Mengzhou Xia, Zhepei Wei et al.

reinforcement learningmathematical reasoninglanguage modelspolicy gradients+4

89

ICML 2025arXiv:2412.09078

#62

Forest-of-Thought: Scaling Test-Time Compute for Enhancing LLM Reasoning

Zhenni Bi, Kai Han, Chuanjian Liu et al.

89

NEURIPS 2025arXiv:2504.12216

#63

d1: Scaling Reasoning in Diffusion Large Language Models via Reinforcement Learning

Siyan Zhao, Devaansh Gupta, Qinqing Zheng et al.

diffusion large language modelsreinforcement learningnon-autoregressive generationreasoning capabilities+4

87

NEURIPS 2025arXiv:2505.14652

#64

General-Reasoner: Advancing LLM Reasoning Across All Domains

Xueguang Ma, Qian Liu, Dongfu Jiang et al.

reinforcement learninglarge language modelsreasoning capabilitiesanswer verification+4

86

ICLR 2024arXiv:2401.12242

#65

BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models

Zhen Xiang, Fengqing Jiang, Zidi Xiong et al.

84

AAAI 2024arXiv:2401.12863

#66

KAM-CoT: Knowledge Augmented Multimodal Chain-of-Thoughts Reasoning

Debjyoti Mondal, Suraj Modi, Subhadarshi Panda et al.

chain-of-thought reasoningmultimodal reasoningknowledge graph integrationlarge language models+3

82

ICLR 2024arXiv:2305.14483

#67

Language Model Self-improvement by Reinforcement Learning Contemplation

Jing-Cheng Pang, Pengyuan Wang, Kaiyuan Li et al.

81

ICLR 2025arXiv:2502.17416

#68

Reasoning with Latent Thoughts: On the Power of Looped Transformers

Nikunj Saunshi, Nishanth Dikkala, Zhiyuan Li et al.

looped transformersreasoning problemslatent thoughtschain-of-thought reasoning+4

79

ICML 2024arXiv:2307.08678

#69

Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations

Yanda Chen, Ruiqi Zhong, Narutatsu Ri et al.

counterfactual simulatabilitynatural language explanationslarge language modelsfactual reasoning+4

79

NEURIPS 2025arXiv:2504.05812

#70

Right Question is Already Half the Answer: Fully Unsupervised LLM Reasoning Incentivization

Qingyang Zhang, Haitao Wu, Changqing Zhang et al.

unsupervised reasoning incentivizationentropy minimizationlatent semantic spacemathematical reasoning+4

78

ICLR 2024arXiv:2307.09476

#71

Overthinking the Truth: Understanding how Language Models Process False Demonstrations

Danny Halawi, Jean-Stanislas Denain, Jacob Steinhardt

73

COLM 2025arXiv:2504.07086

#72

A Sober Look at Progress in Language Model Reasoning: Pitfalls and Paths to Reproducibility

Andreas Hochlehnert, Hardik Bhatnagar, Vishaal Udandarao et al.

data curationrlgrpomath+1

71

ICLR 2025arXiv:2410.21272

#73

Arithmetic Without Algorithms: Language Models Solve Math with a Bag of Heuristics

Yaniv Nikankin, Anja Reusch, Aaron Mueller et al.

70

NEURIPS 2025arXiv:2505.13379

#74

Thinkless: LLM Learns When to Think

Gongfan Fang, Xinyin Ma, Xinchao Wang

chain-of-thought reasoningreasoning language modelsadaptive reasoning selectionreinforcement learning paradigm+4

70

ICML 2025arXiv:2501.11651

#75

T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling

Zhenyu Hou, Xin Lv, Rui Lu et al.

68

ICML 2024arXiv:2404.14662

#76

NExT: Teaching Large Language Models to Reason about Code Execution

Ansong Ni, Miltiadis Allamanis, Arman Cohan et al.

code execution reasoningprogram repairexecution trace analysischain-of-thought rationales+4

65

ICLR 2025arXiv:2501.05707

#77

Multiagent Finetuning: Self Improvement with Diverse Reasoning Chains

Vighnesh Subramaniam, Yilun Du, Joshua B Tenenbaum et al.

63

AAAI 2024arXiv:2312.07399

#78

Large Language Models Are Clinical Reasoners: Reasoning-Aware Diagnosis Framework with Prompt-Generated Rationales

Taeyoon Kwon, Kai Ong, Dongjin Kang et al.

clinical reasoninglarge language modelsdisease diagnosisprompt-based learning+3

62

multimodal large language modelsreasoning-guided generationspatial coordinate reasoningsemantic-spatial guidance+4

#79

GoT: Unleashing Reasoning Capability of MLLM for Visual Generation and Editing

Rongyao Fang, Chengqi Duan, Kun Wang et al.

NEURIPS 2025

60

ICML 2025arXiv:2501.18099

#80

Learning to Plan & Reason for Evaluation with Thinking-LLM-as-a-Judge

Swarnadeep Saha, Xian Li, Marjan Ghazvininejad et al.

60

NEURIPS 2025arXiv:2507.16815

#81

ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent Planning

Chi-Pin Huang, Yueh-Hua Wu, Min-Hung Chen et al.

vision-language-action reasoningreinforced visual planningembodied reasoning plansmultimodal instruction interpretation+4

59

NEURIPS 2025arXiv:2505.15879

#82

GRIT: Teaching MLLMs to Think with Images

Yue Fan, Xuehai He, Diji Yang et al.

59

ICML 2024arXiv:2402.05808

#83

Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning

Zhiheng Xi, Wenxiang Chen, Boyang Hong et al.

reinforcement learninglarge language modelsreasoning tasksoutcome supervision+4

58

NEURIPS 2025arXiv:2503.19470

#84

ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning

Mingyang Chen, Linzhuang Sun, Tianpeng Li et al.

reasoning with searchreinforcement learningmulti-hop question answeringsearch-guided reasoning+3

57

ICLR 2025arXiv:2407.10805

#85

Think-on-Graph 2.0: Deep and Faithful Large Language Model Reasoning with Knowledge-guided Retrieval Augmented Generation

Shengjie Ma, Chengjin Xu, Xuhui Jiang et al.

54

NEURIPS 2025arXiv:2506.09965

#86

Reinforcing Spatial Reasoning in Vision-Language Models with Interwoven Thinking and Visual Drawing

Junfei Wu, Jian Guan, Kaituo Feng et al.

54

AAAI 2024arXiv:2401.03991

#87

Advancing Spatial Reasoning in Large Language Models: An In-Depth Evaluation and Enhancement Using the StepGame Benchmark

Fangjun Li, David C. Hogg, Anthony G. Cohn

spatial reasoninglarge language modelsbenchmark evaluationtemplate-to-relation mapping+4

53

ICML 2025arXiv:2502.03275

#88

Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning

Andy (DiJia) Su, Hanlin Zhu, Yingchen Xu et al.

NEURIPS 2025arXiv:2505.07686

#89

S-GRPO: Early Exit via Reinforcement Learning in Reasoning Models

Muzhi Dai, Chenxu Yang, Qingyi Si

early exit mechanismschain-of-thought generationreasoning modelsreinforcement learning paradigm+4

Code GenerationCode ReasoningLarge Language ModelLiveCodeBench

#90

OpenCodeReasoning: Advancing Data Distillation for Competitive Coding

Wasi Uddin Ahmad, Sean Narenthiran, Somshubra Majumdar et al.

COLM 2025

ICML 2024arXiv:2402.08939

#91

Premise Order Matters in Reasoning with Large Language Models

Xinyun Chen, Ryan Chi, Xuezhi Wang et al.

premise ordering effectdeductive reasoningmathematical problem-solvinglarge language models+3

ICML 2025arXiv:2411.19943

#92

Critical Tokens Matter: Token-Level Contrastive Estimation Enhances LLM’s Reasoning Capability

Zicheng Lin, Tian Liang, Jiahao Xu et al.

51

ICLR 2025arXiv:2407.10040

#93

Lean-STaR: Learning to Interleave Thinking and Proving

Haohan Lin, Zhiqing Sun, Sean Welleck et al.

51

ICLR 2025arXiv:2410.08815

#94

StructRAG: Boosting Knowledge Intensive Reasoning of LLMs via Inference-time Hybrid Information Structurization

Zhuoqun Li, Xuanang Chen, Haiyang Yu et al.

retrieval-augmented generationknowledge-intensive reasoninginformation structurizationlarge language models+3

51

ICLR 2025arXiv:2408.16293

#95

Physics of Language Models: Part 2.2, How to Learn From Mistakes on Grade-School Math Problems

Tian Ye, Zicheng Xu, Yuanzhi Li et al.

50

NEURIPS 2025arXiv:2502.12018

#96

Atom of Thoughts for Markov LLM Test-Time Scaling

Fengwei Teng, Quan Shi, Zhaoyang Yu et al.

test-time scalingmarkovian reasoning processreasoning trajectoriestree search integration+3

COLM 2025arXiv:2504.15466

#97

Learning Adaptive Parallel Reasoning with Language Models

Jiayi Pan, Xiuyu Li, Long Lian et al.

large language modelsreasoning

AAAI 2025arXiv:2408.09698

#98

Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation

Yuyang Ye, Zhi Zheng, Yishan Shen et al.

NEURIPS 2025arXiv:2505.03318

#99

Unified Multimodal Chain-of-Thought Reward Model through Reinforcement Fine-Tuning

Yibin Wang, li zhimin, Yuhang Zang et al.

NEURIPS 2025arXiv:2505.15778

#100

Soft Thinking: Unlocking the Reasoning Potential of LLMs in Continuous Concept Space

Zhen Zhang, Xuehai He, Weixiang Yan et al.

continuous concept spaceabstract concept tokensreasoning modelstoken embeddings+4

48