136 citations · 563 across the 31 of their papers we have counts for
5 papers · 2 filters
Reward Gaming in Conditional Text Generation
Richard Yuanzhe Pang, Vishakh Padmakumar, Thibault Sellam +2
To align conditional text generation model outputs with desired behaviors, there has been an increasing focus on training the model using reinforcement learning (RL) with reward fu…
Robustification of Multilingual Language Models to Real-world Noise in Crosslingual Zero-shot Settings with Robust Contrastive Pretraining
Asa Cooper Stickland, Sailik Sengupta, Jason Krone +2
Advances in neural modeling have achieved state-of-the-art (SOTA) results on public natural language processing (NLP) benchmarks, at times surpassing human performance. However, th…
Language Models Are Greedy Reasoners: A Systematic Formal Analysis of Chain-of-Thought
Abulhair Saparov, He He
Large language models (LLMs) have shown remarkable reasoning capabilities given chain-of-thought prompts (examples with intermediate reasoning steps). Existing benchmarks measure r…
On the Relation between Sensitivity and Accuracy in In-context Learning
Yanda Chen, Chen Zhao, Zhou Yu +2
In-context learning (ICL) suffers from oversensitivity to the prompt, making it unreliable in real-world scenarios. We study the sensitivity of ICL with respect to multiple perturb…
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning
Vishakh Padmakumar, Leonard Lausen, Miguel Ballesteros +3
Recent work has found that multi-task training with a large number of diverse tasks can uniformly improve downstream performance on unseen target tasks. In contrast, literature on…