collaborators

11 papers

cs.DS2026

Compact Path Representation in DAGs via Colored Edge Pebbling

Paola Bonizzoni, Alessio Conte, Gianluca Della Vedova +3

Compactly representing a variation graph is a core problem in computational pangenomics that is usually attacked with techniques that have been originated on texts and adapted to g…

cs.CL2026

Emulate or Estimate? The Divergent Strengths of Base and Post-Trained Language Models for Opinion Simulation

Seth Grief-Albert, Jessica Bo, Difan Jiao +1

Large language models are increasingly used to simulate human opinions, but prior work reports conflicting results: some studies find promising alignment with human survey data, wh…

cs.AI2026

Tandem Reinforcement Learning with Verifiable Rewards

Difan Jiao, Raghav Singhal, Robert West +1

Reinforcement learning with verifiable rewards (RLVR) has significantly improved the reasoning capability of large language models, reaching expert or even superhuman performance i…

cs.IR2026

SafeGEO: Understanding Generative Engine Optimization Risks in Recommendation Agents

Qianfeng Wen, Yifan Simon Liu, Xin Liu +4

Generative Engine Optimization (GEO) lets content owners rewrite web content to increase their visibility in generative systems. In recommendation agents, this creates a risk that…

cs.LG2026

MINER: Mining Multimodal Internal Representation for Efficient Retrieval

Weien Li, Rui Song, Zeyu Li +8

Visual document retrieval has become essential for accessing information in visually rich documents. Existing approaches fall into two camps. Late-interaction retrievers achieve st…

cs.AI2026

LLM Safety From Within: Detecting Harmful Content with Internal Representations

Difan Jiao, Yilun Liu, Ye Yuan +4

Guard models are widely used to detect harmful content in user prompts and LLM responses. However, state-of-the-art guard models rely solely on terminal-layer representations and o…