Andi Peng
Andi Peng has 2 papers in our library, in 2024–2026; often with Alex Gu, Alexis Ross, Chenglei Si.
OpenAlex · ORCID · Wikidata · h-index 7 · 22 works · 284 citations OpenAlex, 2026-10-14
📄 2 works in our library · 🔗 Cited 32 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #10504
Affiliations
🎓Massachusetts Institute of TechnologyCambridge ·
United States2022–2026 · 11 papersEmployment🔬MIT Computer Science and Artificial Intelligence LaboratoryCambridge ·
United States2023–2026 · 2 papers🏢MicrosoftRedmond ·
United States2019–2020 · 4 papers
Fields, topics and concepts
📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works
Works by year
2020s
Papers
- Learning How Hard to Think: Input-Adaptive Allocation of LM Computation (2024 · 22 citations)
Costly decoding strategies such as best-of-k sampling with reranking, or calling a stronger model, improve LM outputs, but they are usually applied uniformly to every query. - Scaling Collaborative Effort with Agents (2026 · 7 citations)
This position paper argues that LLM agents are mostly built and judged as one-shot task finishers. That suits poorly the many real tasks where user goals are vague and change as work proceeds. The authors present five case studies (data analysis, travel planning, financial advising, education, math discovery). In…
All works
- Learning How Hard to Think: Input-Adaptive Allocation of LM ComputationarXiv:2410.04707Mehul Damani, Idan Shenfeld, Andi Peng, et al.2024 · 22 citations
- Scaling Collaborative Effort with AgentsFindings of the Association for Computational LinguisticsShannon Zejiang Shen, Valerie Chen, Ken Gu, et al.2026 · 7 citations
- Stress-Testing Model Specs Reveals Character Differences among Language Models ↗arXiv (Cornell University) · no summary yetZhang, Jifan et al.2025 · 4 citations
Co-authors here
Venues
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
Cited by
Updated
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