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Found 10 papers, 5 papers with code
Predicting Sentence Deletions for Text Simplification Using a Functional Discourse Structure
Document-level text simplification often deletes some sentences besides performing lexical, grammatical or structural simplification to reduce text complexity.
Classification without (Proper) Representation: Political Heterogeneity in Social Media and Its Implications for Classification and Behavioral Analysis
Reddit is home to a broad spectrum of political activity, and users signal their political affiliations in multiple ways—from self-declarations to community participation.
Causal Inference for Human-Language Model Collaboration
A key challenge in answering this causal inference question is formulating an appropriate causal estimand: the conventional average treatment effect (ATE) estimand is inapplicable to text-based treatments due to their high dimensionality.
TableLLM: Enabling Tabular Data Manipulation by LLMs in Real Office Usage Scenarios
We introduce TableLLM, a robust large language model (LLM) with 13 billion parameters, purpose-built for proficiently handling tabular data manipulation tasks, whether they are embedded within documents or spreadsheets, catering to real-world office scenarios.
Who should I Collaborate with? A Comparative Study of Academia and Industry Research Collaboration in NLP
The goal of our research was to investigate the effects of collaboration between academia and industry on Natural Language Processing (NLP).
Ranking & Reweighting Improves Group Distributional Robustness
Recent work has shown that standard training via empirical risk minimization (ERM) can produce models that achieve high accuracy on average but low accuracy on underrepresented groups due to the prevalence of spurious features.
Optimal reconciliation with immutable forecasts
In this paper, we formulate reconciliation methodology that keeps forecasts of a pre-specified subset of variables unchanged or "immutable".
DyRep: Bootstrapping Training with Dynamic Re-parameterization
Structural re-parameterization (Rep) methods achieve noticeable improvements on simple VGG-style networks.
MeetSum: Transforming Meeting Transcript Summarization using Transformers!
We test our model on a testing set from the AMI dataset and report the ROUGE-2 score of the generated summary to compare with previous literature.
Single-Shot Motion Completion with Transformer
Motion completion is a challenging and long-discussed problem, which is of great significance in film and game applications.
Ranked #2 on
Motion Synthesis
on LaFAN1
