Mitigating Exploration Bias in RL for Multi-Instruction Following

arXiv:2608.23830 · cs.CL, cs.LG · Submitted 2026-08-24 · Read on arXiv

cs.CL, cs.LG

Submitted: 2026-08-24

Updated: 2026-08-24

Code: https://github.com/mianzhang/MulIF

Terminology

Accuracy — 33× in this paper · explained in 1 episode
Reinforcement Learning — 10× in this paper · explained in 4 episodes
Benchmark — 9× in this paper · explained in 2 episodes
Verification — 6× in this paper · explained in 2 episodes
Ablation — 4× in this paper · explained in 1 episode
Benchmarking — 4× in this paper · explained in 3 episodes
Fine-Tuning — 4× in this paper · explained in 5 episodes
Reward Function — 4× in this paper · explained in 2 episodes
Two-Stage Framework — 4× in this paper · explained in 2 episodes
GRPO — 3× in this paper · explained in 6 episodes
Variation of Instruction Accuracy — 3× in this paper
Verifier — 3× in this paper · explained in 2 episodes
Entropy Collapse — 2× in this paper · explained in 2 episodes
Ablation Studies — 1× in this paper · explained in 1 episode
Ablation study — 1× in this paper · explained in 1 episode
Alignment — 1× in this paper · explained in 1 episode
Clustering — 1× in this paper · explained in 2 episodes
Core — 1× in this paper · explained in 2 episodes
Generalization — 1× in this paper · explained in 13 episodes
Instruction Coverage Rate — 1× in this paper
Instruction Tuning — 1× in this paper · explained in 2 episodes
Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
Mode Collapse — 1× in this paper · explained in 2 episodes
Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
Thinking mode — 1× in this paper · explained in 2 episodes
Variance of Synergy Accuracy — 1× in this paper

Terminology

Related papers