Accepted Papers

Oral Presentation

• From Causal to Concept-Based Representation Learning

• Using Relational and Causality Context for Tasks with Specialized Vocabularies that are Challenging for LLMs

• Causally Testing Gender Bias in LLMs: A Case Study on Occupational Bias

• Causal Order: The Key to Leveraging Imperfect Experts in Causal Inference

Poster Presentation

• CausalQuest: Collecting Natural Causal Questions for AI Agents

• A Causal Perspective in Brainwave Foundation Models

• Interactive Semantic Interventions for VLMs: A Causality-Inspired Investigation of VLM Failures

• Estimating Effects of Tokens in Preference Learning

• Competence-Based Analysis of Language Models

• CausalBench: A Comprehensive Benchmark for Evaluating Causal Reasoning Capabilities of Large Language Models

• Reasoning with a Few Good Cross-Questions Greatly Enhances Causal Event Attribution in LLMs

• LLM-initialized Differentiable Causal Discovery

• Counterfactual Causal Inference in Natural Language with Large Language Models

• From Correlation to Causation: Understanding Climate Change through ML and LLM Inquiries

• Are UFOs Driving Innovation? The Illusion of Causality in Large Language Models

• Evaluating Interventional Reasoning Capabilities of Large Language Models

• CodeSCM: Causal Analysis for Multi-Modal Code Generation

• Counterfactual Token Generation in Large Language Models

• Hypothesizing Missing Causal Variables with LLMs

• Investigating Causal Reasoning in Large Language Models

• CausalGraph2LLM: Evaluating LLMs for Causal Queries

• On Incorporating Prior Knowledge Extracted from Pre-trained Language Models into Causal Discovery

• Leveraging LLM-Generated Structural Prior for Causal Inference with Concurrent Causes

• Causal Reasoning in Large Language Models: A Knowledge Graph Approach

• Are Police Biased? An NLP Approach

• On LLM Augmented AB Experimentation

• Causal Interventions on Causal Paths: Mapping GPT-2’s Reasoning From Syntax to Semantics

• Teaching Transformers Causal Reasoning through Axiomatic Training

• Causal World Representation in the GPT Model

• Can large language models reason about causal relationships in multimodal time series data?