activity
20242026
collaborators

8 papers

cs.AI2026

TRIM: Hybrid Inference via Targeted Stepwise Routing in Multi-Step Reasoning Tasks

Vansh Kapoor, Aman Gupta, Hao Chen +3

Multi-step reasoning tasks like mathematical problem solving are vulnerable to cascading failures, where a single incorrect step leads to complete solution breakdown. Current LLM r…

cs.CL2025

TOD-ProcBench: Benchmarking Complex Instruction-Following in Task-Oriented Dialogues

Sarik Ghazarian, Abhinav Gullapalli, Swair Shah +4

In real-world task-oriented dialogue (TOD) settings, agents are required to strictly adhere to complex instructions while conducting multi-turn conversations with customers. These…

cs.CL2025

How and Where to Translate? The Impact of Translation Strategies in Cross-lingual LLM Prompting

Aman Gupta, Yingying Zhuang, Zhou Yu +2

Despite advances in the multilingual capabilities of Large Language Models (LLMs), their performance varies substantially across different languages and tasks. In multilingual retr…

cs.CL2025

Multilingual Information Retrieval with a Monolingual Knowledge Base

Yingying Zhuang, Aman Gupta, Anurag Beniwal

Multilingual information retrieval has emerged as powerful tools for expanding knowledge sharing across languages. On the other hand, resources on high quality knowledge base are o…

cs.CL2025

REIC: RAG-Enhanced Intent Classification at Scale

Ziji Zhang, Michael Yang, Zhiyu Chen +6

Accurate intent classification is critical for efficient routing in customer service, ensuring customers are connected with the most suitable agents while reducing handling times a…

cs.CL2025

When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMs

Xiaomin Li, Zhou Yu, Zhiwei Zhang +5

Reasoning-enhanced large language models (RLLMs), whether explicitly trained for reasoning or prompted via chain-of-thought (CoT), have achieved state-of-the-art performance on man…