8 citations · 17 across the 14 of their papers we have counts for
12 papers · 1 filter
PARSER: Read in Parallel, Reason in Depth for Long-Context LLM Agents
Kun Li, Zexuan Qiu, Tianhua Zhang +2
Sequential memory agents process long documents by reading chunks one after another while maintaining a compact memory state, coupling document traversal to reasoning depth. This c…
TriggerBench: Investigating Prospective Memory for Large Language Models
Tianhua Zhang, Xinjiang Wang, Qianxi Zhang +6
While Large Language Models (LLMs) are increasingly deployed in long interactions, existing evaluations focus predominantly on retrospective memory (RM) via explicit queries. Prosp…
TreePS-RAG: Tree-based Process Supervision for Reinforcement Learning in Agentic RAG
Tianhua Zhang, Kun Li, Junan Li +5
Agentic retrieval-augmented generation (RAG) formulates question answering as a multi-step interaction between reasoning and information retrieval, and has recently been advanced b…
MMSU: A Massive Multi-task Spoken Language Understanding and Reasoning Benchmark
Dingdong Wang, Junan Li, Jincenzi Wu +4
Speech inherently contains rich acoustic information that extends far beyond the textual language. In real-world spoken language understanding, effective interpretation often requi…
RAG-Zeval: Towards Robust and Interpretable Evaluation on RAG Responses through End-to-End Rule-Guided Reasoning
Kun Li, Yunxiang Li, Tianhua Zhang +4
Robust evaluation is critical for deploying trustworthy retrieval-augmented generation (RAG) systems. However, current LLM-based evaluation frameworks predominantly rely on directl…
Generate, Discriminate, Evolve: Enhancing Context Faithfulness via Fine-Grained Sentence-Level Self-Evolution
Kun Li, Tianhua Zhang, Yunxiang Li +5
Improving context faithfulness in large language models is essential for developing trustworthy retrieval augmented generation systems and mitigating hallucinations, especially in…
Decoding on Graphs: Faithful and Sound Reasoning on Knowledge Graphs through Generation of Well-Formed Chains
Kun Li, Tianhua Zhang, Xixin Wu +3
Knowledge Graphs (KGs) can serve as reliable knowledge sources for question answering (QA) due to their structured representation of knowledge. Existing research on the utilization…
Adaptive Query Rewriting: Aligning Rewriters through Marginal Probability of Conversational Answers
Tianhua Zhang, Kun Li, Hongyin Luo +3
Query rewriting is a crucial technique for passage retrieval in open-domain conversational question answering (CQA). It decontexualizes conversational queries into self-contained q…
Natural Language Embedded Programs for Hybrid Language Symbolic Reasoning
Tianhua Zhang, Jiaxin Ge, Hongyin Luo +7
How can we perform computations over natural language representations to solve tasks that require symbolic and numeric reasoning? We propose natural language embedded programs (NLE…
SAIL: Search-Augmented Instruction Learning
Hongyin Luo, Yung-Sung Chuang, Yuan Gong +6
Large language models (LLMs) have been significantly improved by instruction fine-tuning, but still lack transparency and the ability to utilize up-to-date knowledge and informatio…
Interpretable Unified Language Checking
Tianhua Zhang, Hongyin Luo, Yung-Sung Chuang +7
Despite recent concerns about undesirable behaviors generated by large language models (LLMs), including non-factual, biased, and hateful language, we find LLMs are inherent multi-…
Unstructured Knowledge Access in Task-oriented Dialog Modeling using Language Inference, Knowledge Retrieval and Knowledge-Integrative Response Generation
Mudit Chaudhary, Borislav Dzodzo, Sida Huang +10
Dialog systems enriched with external knowledge can handle user queries that are outside the scope of the supporting databases/APIs. In this paper, we follow the baseline provided…