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cs.CL2026

QUEST: Training Frontier Deep Research Agents with Fully Synthetic Tasks

Jian Xie, Tianhe Lin, Zilu Wang +16

Deep research agents extend the role of search engines from retrieving keyword-matched pages to synthesizing knowledge, fundamentally changing how humans interact with information.…

cs.CL2024

TravelPlanner: A Benchmark for Real-World Planning with Language Agents

Jian Xie, Kai Zhang, Jiangjie Chen +5

Planning has been part of the core pursuit for artificial intelligence since its conception, but earlier AI agents mostly focused on constrained settings because many of the cognit…

cs.CL2024

Deductive Beam Search: Decoding Deducible Rationale for Chain-of-Thought Reasoning

Tinghui Zhu, Kai Zhang, Jian Xie +1

Recent advancements have significantly augmented the reasoning capabilities of Large Language Models (LLMs) through various methodologies, especially chain-of-thought (CoT) reasoni…

cs.CL2024

How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?

Siye Wu, Jian Xie, Jiangjie Chen +3

By leveraging the retrieval of information from external knowledge databases, Large Language Models (LLMs) exhibit enhanced capabilities for accomplishing many knowledge-intensive…

cs.CL2024

MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI

Xiang Yue, Yuansheng Ni, Kai Zhang +19

We introduce MMMU: a new benchmark designed to evaluate multimodal models on massive multi-discipline tasks demanding college-level subject knowledge and deliberate reasoning. MMMU…

cs.CL2024

CIF-Bench: A Chinese Instruction-Following Benchmark for Evaluating the Generalizability of Large Language Models

Yizhi LI, Ge Zhang, Xingwei Qu +16

The advancement of large language models (LLMs) has enhanced the ability to generalize across a wide range of unseen natural language processing (NLP) tasks through instruction-fol…