25 papers
How People Evaluate AI-, Expert-, and Peer-Style Financial Advice
Aryan Ramchandra Kapadia, Eshwar Chandrasekharan, Koustuv Saha
As generative AI increasingly becomes a common source of daily decision-making, including financial choices, it is critical to understand how people evaluate AI-generated financial…
Toxic HallucinAItions: Perturbing Prompts and Tracing LLM Circuits
Soorya Ram Shimgekar, Agam Goyal, Amruta Parulekar +6
Large language models (LLMs) are increasingly deployed in conversational settings where user tone ranges from polite to adversarial or toxic, yet less is known about whether toxic…
LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback
Jiwon Kim, Maya Ajit, Sherry Gong +4
Large language models (LLMs) show promise in generating supportive responses for mental health queries, but improving their usefulness, empathy, and safety often requires substanti…
Algorithmic Cultivation: How Social Media Feeds Shape User Language
Olivia Pal, Agam Goyal, Eshwar Chandrasekharan +1
Algorithmic feeds have become primary environments for encountering information online, yet while they shape what people see, less is known about how sustained feed exposure shapes…
Masking or Mitigating? Deconstructing the Impact of Query Rewriting on Retriever Biases in RAG
Agam Goyal, Koyel Mukherjee, Apoorv Saxena +3
Dense retrievers in retrieval-augmented generation (RAG) systems exhibit systematic biases -- including brevity, position, literal matching, and repetition biases -- that can compr…
From Plausible to Causal: Counterfactual Semantics for Policy Evaluation in Simulated Online Communities
Agam Goyal, Yian Wang, Eshwar Chandrasekharan +1
LLM-based social simulations can generate believable community interactions, enabling ``policy wind tunnels'' where governance interventions are tested before deployment. But belie…