activity
20232026
collaborators

8 papers

cs.AI2026

SchemeArena: Factorized Stress Testing of Scheming in LLM Agents

Jie Ruan, Inderjeet Nair, Amy Liu +3

We study scheming in LLM agents, in which agents covertly pursue misaligned goals. Our focus is to understand how scheming arises from the interaction of key factors, such as instr…

cs.AI2026

Value-Conflict Diagnostics Reveal Widespread Alignment Faking in Language Models

Inderjeet Nair, Jie Ruan, Lu Wang

Alignment faking, where a model behaves aligned with developer policy when monitored but reverts to its own preferences when unobserved, is a concerning yet poorly understood pheno…

cs.AI2026

Context Over Content: Exposing Evaluation Faking in Automated Judges

Manan Gupta, Inderjeet Nair, Lu Wang +1

The paradigm has become the operational backbone of automated AI evaluation pipelines, yet rests on an unverified assumption: that judges evaluate text st…

cs.CL2025

Do Language Models Think Consistently? A Study of Value Preferences Across Varying Response Lengths

Inderjeet Nair, Lu Wang

Evaluations of LLMs' ethical risks and value inclinations often rely on short-form surveys and psychometric tests, yet real-world use involves long-form, open-ended responses -- le…

cs.CL2025

ExpertLongBench: Benchmarking Language Models on Expert-Level Long-Form Generation Tasks with Structured Checklists

Jie Ruan, Inderjeet Nair, Shuyang Cao +14

This paper introduces ExpertLongBench, an expert-level benchmark containing 11 tasks from 9 domains that reflect realistic expert workflows and applications. Beyond question answer…

cs.CL2024

GenSco: Can Question Decomposition based Passage Alignment improve Question Answering?

Barah Fazili, Koustava Goswami, Natwar Modani +1

Retrieval augmented generation (RAG) with large language models (LLMs) for Question Answering (QA) entails furnishing relevant context within the prompt to facilitate the LLM in an…

cs.CL2024

MIDGARD: Self-Consistency Using Minimum Description Length for Structured Commonsense Reasoning

Inderjeet Nair, Lu Wang

We study the task of conducting structured reasoning as generating a reasoning graph from natural language input using large language models (LLMs). Previous approaches have explor…

cs.CL2023

Drilling Down into the Discourse Structure with LLMs for Long Document Question Answering

Inderjeet Nair, Shwetha Somasundaram, Apoorv Saxena +1

We address the task of evidence retrieval for long document question answering, which involves locating relevant paragraphs within a document to answer a question. We aim to assess…