10 papers
Attribution Gradients: Incrementally Unfolding Citations for Critical Examination of Attributed AI Answers
Hita Kambhamettu, Alyssa Hwang, Philippe Laban +1
AI answer engines are a relatively new kind of information search tool: rather than returning a ranked list of documents, they generate an answer to a search question with inline c…
Flipping the Dialogue: Training and Evaluating User Language Models
Tarek Naous, Philippe Laban, Wei Xu +1
Conversations with LMs involve two participants: a human user leading the conversation, and an LM assistant responding to the user's request. To satisfy this specific role, LMs are…
DeepTRACE: Auditing Deep Research AI Systems for Tracking Reliability Across Citations and Evidence
Pranav Narayanan Venkit, Philippe Laban, Yilun Zhou +3
Generative search engines and deep research LLM agents promise trustworthy, source-grounded synthesis, yet users regularly encounter overconfidence, weak sourcing, and confusing ci…
AI-Slop to AI-Polish? Aligning Language Models through Edit-Based Writing Rewards and Test-time Computation
Tuhin Chakrabarty, Philippe Laban, Chien-Sheng Wu
AI-generated text is proliferating across domains, from creative writing and journalism to marketing content and scientific articles. Models can follow user-provided instructions t…
SummExecEdit: A Factual Consistency Benchmark in Summarization with Executable Edits
Onkar Thorat, Philippe Laban, Chien-Sheng Wu
Detecting factual inconsistencies in summarization is critical, yet existing benchmarks lack the necessary challenge and interpretability for robust evaluation. In this paper, we i…
Why Vision Language Models Struggle with Visual Arithmetic? Towards Enhanced Chart and Geometry Understanding
Kung-Hsiang Huang, Can Qin, Haoyi Qiu +4
Vision Language Models (VLMs) have achieved remarkable progress in multimodal tasks, yet they often struggle with visual arithmetic, seemingly simple capabilities like object count…