Hannaneh Hajishirzi

RewardBench 2: Advancing Reward Model Evaluation

RL Grokking Recipe: How Does RL Unlock and Transfer New Algorithms in LLMs?

Spurious Rewards: Rethinking Training Signals in RLVR

Train for Truth, Keep the Skills: Binary Retrieval-Augmented Reward Mitigates Hallucinations

ASTRO: Teaching Language Models to Reason by Reflecting and Backtracking In-Context

FlexOLMo: Open Language Models for Flexible Data Use

EvalTree: Profiling Language Model Weaknesses via Hierarchical Capability Trees

OLMoE: Open Mixture-of-Experts Language Models

Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Critical Batch Size Revisited: A Simple Empirical Approach to Large-Batch Language Model Training

Signal and Noise: A Framework for Reducing Uncertainty in Language Model Evaluation

Fluid Language Model Benchmarking

Answer, Assemble, Ace: Understanding How LMs Answer Multiple Choice Questions

2 OLMo 2 Furious (COLM’s Version)

Establishing Task Scaling Laws via Compute-Efficient Model Ladders

Organize the Web: Constructing Domains Enhances Pre-Training Data Curation

ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data

How Many Van Goghs Does It Take to Van Gogh? Finding the Imitation Threshold

Leveraging Set Assumption for Membership Inference in Language Models

Hybrid Preferences: Learning to Route Instances for Human vs. AI Feedback