Hunter Lang

18 papers · 2018–2026 · 6 conferences · across top CS/AI conferences

Achievements

+8 more ↓

🏃 Academic Marathon (7) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (6) 🐣 Hot Topic Early Bird

🌍 Conference Polyglot (6) 🏃 Academic Marathon (7) 🐝 Cross-Pollinator (13) 🤝 Dynamic Duo (12) 🔥 Unstoppable (5) 💎 Century Club (16) ❓ The Questioner 🗃️ Keyword Collector (71)

Conferences

AISTATS (6) NIPS (4) ACL (3) ICML (3) AAAI (1) EMNLP (1)

Top co-authors

David Sontag (12) Aravindan Vijayaraghavan (6) Yoon Kim (4) Lin Xiao (2) Stefan Hegselmann (2) Monica Agrawal (2) Pengchuan Zhang (2) Yejin Choi (1) Songlin Li (1) Alejandro Buendia (1)

Keywords

large language model (5) map inference (4) few-shot learning (3) zero-shot learning (3) representation learning (2) stochastic gradient descent (2) self-supervised learning (2) learning rate (2) lp relaxation (2) approximate inference (2) weak supervision (2) probabilistic logic (1) structured prediction (1) computer vision (1) reinforcement learning (1) instruction following (1) contrastive learning (1) prompt-based learning (1) convergence analysis (1) semi-supervised learning (1)

Papers

When One LLM Drools, Multi-LLM Collaboration Rules ACL 2026 AdvancedIF: Rubric-Based Benchmarking and Reinforcement Learning for Advancing LLM Instruction Following ACL 2026 On the Duality between Gradient Transformations and Adapters ICML 2025 Theoretical Analysis of Weak-to-Strong Generalization NIPS 2024 Learning to Decode Collaboratively with Multiple Language Models ACL 2024 Who Should Predict? Exact Algorithms For Learning to Defer to Humans AISTATS 2023 TabLLM: Few-shot Classification of Tabular Data with Large Language Models AISTATS 2023 Leveraging Time Irreversibility with Order-Contrastive Pre-training AISTATS 2022 Training Subset Selection for Weak Supervision NIPS 2022 Large language models are few-shot clinical information extractors EMNLP 2022 Co-training Improves Prompt-based Learning for Large Language Models ICML 2022 Self-Supervised Self-Supervision by Combining Deep Learning and Probabilistic Logic AAAI 2021 Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances AISTATS 2021 Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch) ICML 2021 Using Statistics to Automate Stochastic Optimization NIPS 2019 Block Stability for MAP Inference AISTATS 2019 Understanding the Role of Momentum in Stochastic Gradient Methods NIPS 2019 Optimality of Approximate Inference Algorithms on Stable Instances AISTATS 2018