https://github.com/holarissun/prompt-oirl
공식 코드Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
Papers with Code 아카이브
Arithmetic Reasoning
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/imoneoi/openchat
공식 코드OpenChat: Advancing Open-source Language Models with Mixed-Quality Data
https://github.com/joykirat18/syrelm
공식 코드Frugal LMs Trained to Invoke Symbolic Solvers Achieve Parameter-Efficient Arithmetic Reasoning
https://github.com/keitokudo/dentaku_skill_tree
공식 코드Do Deep Neural Networks Capture Compositionality in Arithmetic Reasoning?
https://github.com/kipok/nemo-skills
공식 코드OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset
https://github.com/kojima-takeshi188/zero_shot_cot
공식 코드https://github.com/leesureman/mot
공식 코드https://github.com/lupantech/InterGPS
공식 코드Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning
https://github.com/lupantech/iconqa
공식 코드IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning
https://github.com/mandar-sharma/overcomingbarriers
공식 코드Overcoming Barriers to Skill Injection in Language Modeling: Case Study in Arithmetic
https://github.com/mandar-sharma/skill-lm
공식 코드Learning Non-linguistic Skills without Sacrificing Linguistic Proficiency
https://github.com/mathllm/mathcoder
공식 코드MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
https://github.com/mehdiazarafza/uav-rag
공식 코드https://github.com/meta-math/MetaMath
공식 코드MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
https://github.com/miaoxiong2320/llm-uncertainty
공식 코드Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
https://github.com/microsoft/tora
공식 코드ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
https://github.com/microsoft/tracecodegen
공식 코드Learning Math Reasoning from Self-Sampled Correct and Partially-Correct Solutions
https://github.com/mistralai/mistral-src
공식 코드https://github.com/niansong1996/lever
공식 코드LEVER: Learning to Verify Language-to-Code Generation with Execution
https://github.com/ofa-sys/gsm8k-screl
공식 코드Scaling Relationship on Learning Mathematical Reasoning with Large Language Models
https://github.com/openai/evals
공식 코드https://github.com/osu-nlp-group/reversal-curse-binding
공식 코드https://github.com/pphuc25/distil-cd
공식 코드https://github.com/princeton-nlp/tree-of-thought-llm
공식 코드Tree of Thoughts: Deliberate Problem Solving with Large Language Models
https://github.com/prompteus/calc-x
공식 코드https://github.com/quanta-fine-tuning/quanta
공식 코드QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation
https://github.com/qwenlm/qwen2
공식 코드https://github.com/rarefin/seq_vcr
공식 코드Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
https://github.com/ruili33/sec
공식 코드Are Human-generated Demonstrations Necessary for In-context Learning?
https://github.com/sail-sg/cpo
공식 코드Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs
https://github.com/salesforce/codet5
공식 코드CodeT5+: Open Code Large Language Models for Code Understanding and Generation
https://github.com/sallytan13/teaching-inspired-prompting
공식 코드https://github.com/salt-nlp/dylan
공식 코드A Dynamic LLM-Powered Agent Network for Task-Oriented Agent Collaboration
https://github.com/savadikarc/gift
공식 코드https://github.com/servicenow/workarena
공식 코드WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks
https://github.com/shizhediao/automate-cot
공식 코드Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.