9 papers · 1 filter
Streaming Sequence Transduction through Dynamic Compression
Weiting Tan, Yunmo Chen, Tongfei Chen +5
We introduce STAR (Stream Transduction with Anchor Representations), a novel Transformer-based model designed for efficient sequence-to-sequence transduction over streams. STAR dyn…
BLT: Can Large Language Models Handle Basic Legal Text?
Andrew Blair-Stanek, Nils Holzenberger, Benjamin Van Durme
We find that the best publicly available LLMs like GPT-4 and Claude currently perform poorly on basic legal text handling. This motivates the creation of a benchmark consisting of…
TV-TREES: Multimodal Entailment Trees for Neuro-Symbolic Video Reasoning
Kate Sanders, Nathaniel Weir, Benjamin Van Durme
It is challenging for models to understand complex, multimodal content such as television clips, and this is in part because video-language models often rely on single-modality rea…
Enhancing Systematic Decompositional Natural Language Inference Using Informal Logic
Nathaniel Weir, Kate Sanders, Orion Weller +8
Recent language models enable new opportunities for structured reasoning with text, such as the construction of intuitive, proof-like textual entailment trees without relying on br…
NELLIE: A Neuro-Symbolic Inference Engine for Grounded, Compositional, and Explainable Reasoning
Nathaniel Weir, Peter Clark, Benjamin Van Durme
Our goal is a modern approach to answering questions via systematic reasoning where answers are supported by human interpretable proof trees grounded in an NL corpus of authoritati…
RORA: Robust Free-Text Rationale Evaluation
Zhengping Jiang, Yining Lu, Hanjie Chen +3
Free-text rationales play a pivotal role in explainable NLP, bridging the knowledge and reasoning gaps behind a model's decision-making. However, due to the diversity of potential…