collaborators

17 papers

cs.CL2026

Retrofitting Small Multilingual Models for Retrieval: Matching 7B Performance with 300M Parameters

Lifu Tu, Yingbo Zhou, Semih Yavuz

Training effective multilingual embedding models presents unique challenges due to the diversity of languages and task objectives. Although small multilingual models (<1 B paramete…

cs.SE2026

SweRank: Software Issue Localization with Code Ranking

Revanth Gangi Reddy, Tarun Suresh, JaeHyeok Doo +7

Software issue localization, the task of identifying the precise code locations (files, classes, or functions) relevant to a natural language issue description (e.g., bug report, f…

cs.AI2026

MAS-ProVe: Understanding the Process Verification of Multi-Agent Systems

Vishal Venkataramani, Haizhou Shi, Zixuan Ke +6

Multi-Agent Systems (MAS) built on Large Language Models (LLMs) often exhibit high variance in their reasoning trajectories. Process verification, which evaluates intermediate step…

cs.SE2025

SweRank+: Multilingual, Multi-Turn Code Ranking for Software Issue Localization

Revanth Gangi Reddy, Ye Liu, Wenting Zhao +7

Maintaining large-scale, multilingual codebases hinges on accurately localizing issues, which requires mapping natural-language error descriptions to the relevant functions that ne…

cs.CL2025

SSR: Socratic Self-Refine for Large Language Model Reasoning

Haizhou Shi, Ye Liu, Bo Pang +6

Large Language Models (LLMs) have demonstrated remarkable reasoning abilities, yet existing test-time frameworks often rely on coarse self-verification and self-correction, limitin…

cs.AI2025

Self-Abstraction from Grounded Experience for Plan-Guided Policy Refinement

Hiroaki Hayashi, Bo Pang, Wenting Zhao +6

Large language model (LLM) based agents are increasingly used to tackle software engineering tasks that require multi-step reasoning and code modification, demonstrating promising…