- CiteLLM: An Agentic Platform for Trustworthy Scientific Reference Discovery
Mengze Hong, Di Jiang, Chen Jason Zhang, Zichang Guo, Yawen Li · Feb 26, 2026 · Citations: 0
Simulation Env
In this work, we present CiteLLM, a specialized agentic platform designed to enable trustworthy reference discovery for grounding author-drafted claims and statements.
- Search-P1: Path-Centric Reward Shaping for Stable and Efficient Agentic RAG Training
Tianle Xia, Ming Xu, Lingxiang Hu, Yiding Sun, Wenwei Li · Feb 26, 2026 · Citations: 0
Automatic Metrics Long Horizon
Agentic RAG addresses this by enabling LLMs to dynamically decide when and what to retrieve, but current RL-based training methods suffer from sparse outcome rewards that discard intermediate signals and low sample efficiency where failed s
- LiCQA : A Lightweight Complex Question Answering System
Sourav Saha, Dwaipayan Roy, Mandar Mitra · Feb 25, 2026 · Citations: 0
Automatic Metrics
The results of our experiments show that LiCQA significantly outperforms these two state-of-the-art systems on benchmark data with noteworthy reduction in latency.
- Retrieval Challenges in Low-Resource Public Service Information: A Case Study on Food Pantry Access
Touseef Hasan, Laila Cure, Souvika Sarkar · Feb 25, 2026 · Citations: 0
Simulation Env
We conduct a pilot evaluation study using community-sourced queries to examine system behavior in realistic scenarios.
- Revisiting RAG Retrievers: An Information Theoretic Benchmark
Wenqing Zheng, Dmitri Kalaev, Noah Fatsi, Daniel Barcklow, Owen Reinert · Feb 25, 2026 · Citations: 0
Automatic Metrics
Existing benchmarks primarily compare entire RAG pipelines or introduce new datasets, providing little guidance on selecting or combining retrievers themselves.
- Revisiting Text Ranking in Deep Research
Chuan Meng, Litu Ou, Sean MacAvaney, Jeff Dalton · Feb 25, 2026 · Citations: 0
Automatic Metrics
To tackle it, most prior work equips large language model (LLM)-based agents with opaque web search APIs, enabling agents to iteratively issue search queries, retrieve external evidence, and reason over it.
- Position-Aware Sequential Attention for Accurate Next Item Recommendations
Timur Nabiev, Evgeny Frolov · Feb 24, 2026 · Citations: 0
Automatic Metrics
Experiments on standard next-item prediction benchmarks show that our positional kernel attention consistently improves over strong competing baselines.
- Generative Pseudo-Labeling for Pre-Ranking with LLMs
Junyu Bi, Xinting Niu, Daixuan Cheng, Kun Yuan, Tao Wang · Feb 24, 2026 · Citations: 0
Automatic Metrics
Pre-ranking is a critical stage in industrial recommendation systems, tasked with efficiently scoring thousands of recalled items for downstream ranking.
- E-MMKGR: A Unified Multimodal Knowledge Graph Framework for E-commerce Applications
Jiwoo Kang, Yeon-Chang Lee · Feb 24, 2026 · Citations: 0
Automatic Metrics
Multimodal recommender systems (MMRSs) enhance collaborative filtering by leveraging item-side modalities, but their reliance on a fixed set of modalities and task-specific objectives limits both modality extensibility and task generalizati
- RMIT-ADM+S at the MMU-RAG NeurIPS 2025 Competition
Kun Ran, Marwah Alaofi, Danula Hettiachchi, Chenglong Ma, Khoi Nguyen Dinh Anh · Feb 24, 2026 · Citations: 0
Automatic Metrics
R2RAG won the Best Dynamic Evaluation award in the Open Source category, demonstrating high effectiveness with careful design and efficient use of resources.
- Unlocking Multimodal Document Intelligence: From Current Triumphs to Future Frontiers of Visual Document Retrieval
Yibo Yan, Jiahao Huo, Guanbo Feng, Mingdong Ou, Yi Cao · Feb 23, 2026 · Citations: 0
Automatic Metrics
We begin by examining the benchmark landscape, and subsequently dive into the methodological evolution, categorizing approaches into three primary aspects: multimodal embedding models, multimodal reranker models, and the integration of Retr
- Sculpting the Vector Space: Towards Efficient Multi-Vector Visual Document Retrieval via Prune-then-Merge Framework
Yibo Yan, Mingdong Ou, Yi Cao, Xin Zou, Jiahao Huo · Feb 23, 2026 · Citations: 0
Automatic Metrics
Visual Document Retrieval (VDR), which aims to retrieve relevant pages within vast corpora of visually-rich documents, is of significance in current multimodal retrieval applications.
- Hyper-KGGen: A Skill-Driven Knowledge Extractor for High-Quality Knowledge Hypergraph Generation
Rizhuo Huang, Yifan Feng, Rundong Xue, Shihui Ying, Jun-Hai Yong · Feb 23, 2026 · Citations: 0
Expert Verification Automatic Metrics
Additionally, we present \textbf{HyperDocRED}, a rigorously annotated benchmark for document-level knowledge hypergraph extraction.
- PerSoMed: A Large-Scale Balanced Dataset for Persian Social Media Text Classification
Isun Chehreh, Ebrahim Ansari · Feb 22, 2026 · Citations: 0
Automatic Metrics
Data collection involved 60,000 raw posts from various Persian social media platforms, followed by rigorous preprocessing and hybrid annotation combining ChatGPT-based few-shot prompting with human verification.
- Learning to Reason for Multi-Step Retrieval of Personal Context in Personalized Question Answering
Maryam Amirizaniani, Alireza Salemi, Hamed Zamani · Feb 22, 2026 · Citations: 0
Pairwise Preference Automatic Metrics Long Horizon
Personalization in Question Answering (QA) requires answers that are both accurate and aligned with users' background, preferences, and historical context.
- Diagnosing LLM Reranker Behavior Under Fixed Evidence Pools
Baris Arat, Emre Sefer · Feb 20, 2026 · Citations: 0
Automatic Metrics
Standard reranking evaluations study how a reranker orders candidates returned by an upstream retriever.
- RVR: Retrieve-Verify-Retrieve for Comprehensive Question Answering
Deniz Qian, Hung-Ting Chen, Eunsol Choi · Feb 20, 2026 · Citations: 0
Automatic Metrics
Our method outperforms baselines, including agentic search approaches, achieving at least 10% relative and 3% absolute gain in complete recall percentage on a multi-answer retrieval dataset (QAMPARI).
- Evaluating Chain-of-Thought Reasoning through Reusability and Verifiability
Shashank Aggarwal, Ram Vikas Mishra, Amit Awekar · Feb 19, 2026 · Citations: 0
Automatic Metrics Multi Agent
In multi-agent IR pipelines for tasks such as search and ranking, LLM-based agents exchange intermediate reasoning in terms of Chain-of-Thought (CoT) with each other.
- ScrapeGraphAI-100k: A Large-Scale Dataset for LLM-Based Web Information Extraction
William Brach, Francesco Zuppichini, Marco Vinciguerra, Lorenzo Padoan · Feb 16, 2026 · Citations: 0
Automatic Metrics
ScrapeGraphAI-100k enables fine-tuning small models, benchmarking structured extraction, and studying schema induction for web IR indexing, and is publicly available on HuggingFace.
- Learning User Interests via Reasoning and Distillation for Cross-Domain News Recommendation
Mengdan Zhu, Yufan Zhao, Tao Di, Yulan Yan, Liang Zhao · Feb 16, 2026 · Citations: 0
Automatic Metrics
News recommendation plays a critical role in online news platforms by helping users discover relevant content.
- Neurosymbolic Retrievers for Retrieval-augmented Generation
Yash Saxena, Manas Gaur · Jan 8, 2026 · Citations: 0
Automatic Metrics
Retrieval Augmented Generation (RAG) has made significant strides in overcoming key limitations of large language models, such as hallucination, lack of contextual grounding, and issues with transparency.
- RAIR: A Rule-Aware Benchmark Uniting Challenging Long-Tail and Visual Salience Subset for E-commerce Relevance Assessment
Chenji Lu, Zhuo Chen, Hui Zhao, Zhenyi Wang, Pengjie Wang · Dec 31, 2025 · Citations: 0
Automatic Metrics
While large language models (LLMs) have shown significant results on relevance task, existing benchmarks lack sufficient complexity for comprehensive model assessment, resulting in an absence of standardized relevance evaluation metrics acr
- Beyond a Million Tokens: Benchmarking and Enhancing Long-Term Memory in LLMs
Mohammad Tavakoli, Alireza Salemi, Carrie Ye, Mohamed Abdalla, Hamed Zamani · Oct 31, 2025 · Citations: 0
Automatic Metrics
Evaluating the abilities of large language models (LLMs) for tasks that require long-term memory and thus long-context reasoning, for example in conversational settings, is hampered by the existing benchmarks, which often lack narrative coh
- LUMI: Unsupervised Intent Clustering with Multiple Pseudo-Labels
I-Fan Lin, Faegheh Hasibi, Suzan Verberne · Oct 16, 2025 · Citations: 0
Automatic Metrics
Our evaluation on four benchmark sets shows that our approach achieves competitive results, better than recent state-of-the-art baselines, while avoiding the need to estimate the number of clusters during embedding refinement, as is require
- Peeking inside the Black-Box: Reinforcement Learning for Explainable and Accurate Relation Extraction
Xinyu Guo, Zhengliang Shi, Minglai Yang, Mahdi Rahimi, Mihai Surdeanu · Oct 7, 2025 · Citations: 0
Human EvalAutomatic Metrics
Finally, human evaluation shows that our best model generates relational keywords closely aligned with gold labels, increasing human explanation quality ratings by 54% (relative).
- AgentDR: Dynamic Recommendation with Implicit Item-Item Relations via LLM-based Agents
Mingdai Yang, Nurendra Choudhary, Jiangshu Du, Edward W. Huang, Philip S. Yu · Oct 7, 2025 · Citations: 0
Automatic Metrics
Recent agent-based recommendation frameworks aim to simulate user behaviors by incorporating memory mechanisms and prompting strategies, but they struggle with hallucinating non-existent items and full-catalog ranking.
- TASER: Table Agents for Schema-guided Extraction and Recommendation
Nicole Cho, Kirsty Fielding, William Watson, Sumitra Ganesh, Manuela Veloso · Aug 18, 2025 · Citations: 0
Critique Edit Automatic Metrics
To address this, we present TASER (Table Agents for Schema-guided Extraction and Recommendation), a continuously learning, agentic table extraction system that converts highly unstructured, multi-page, heterogeneous tables into normalized,
- PersonalAI: A Systematic Comparison of Knowledge Graph Storage and Retrieval Approaches for Personalized LLM agents
Mikhail Menschikov, Dmitry Evseev, Victoria Dochkina, Ruslan Kostoev, Ilia Perepechkin · Jun 20, 2025 · Citations: 0
Automatic Metrics
We evaluate our system on three benchmarks: TriviaQA, HotpotQA, DiaASQ and demonstrate that different memory and retrieval configurations yield optimal performance depending on the task.
- Toward Safe and Human-Aligned Game Conversational Recommendation via Multi-Agent Decomposition
Zheng Hui, Xiaokai Wei, Yexi Jiang, Kevin Gao, Chen Wang · Apr 26, 2025 · Citations: 0
Pairwise Preference Automatic Metrics Multi Agent
These domains typically involve fixed content and passive consumption, where user preferences can be matched by genre or theme.
- PII-Bench: Evaluating Query-Aware Privacy Protection Systems
Hao Shen, Zhouhong Gu, Haokai Hong, Weili Han · Feb 25, 2025 · Citations: 0
Automatic Metrics
To address this challenge, we propose a query-unrelated PII masking strategy and introduce PII-Bench, the first comprehensive evaluation framework for assessing privacy protection systems.
- Causal Claims in Economics
Prashant Garg, Thiemo Fetzer · Jan 12, 2025 · Citations: 0
Automatic Metrics
As economics scales, a key bottleneck is representing what papers claim in a comparable, aggregable form.
- Augmenting Lateral Thinking in Language Models with Humor and Riddle Data for the BRAINTEASER Task
Mina Ghashami, Soumya Smruti Mishra · May 16, 2024 · Citations: 0
Automatic Metrics
The SemEval 2024 BRAINTEASER task challenges language models to perform lateral thinking -- a form of creative, non-linear reasoning that remains underexplored in NLP.
- Improving Stance Detection by Leveraging Measurement Knowledge from Social Sciences: A Case Study of Dutch Political Tweets and Traditional Gender Role Division
Qixiang Fang, Anastasia Giachanou, Ayoub Bagheri · Dec 13, 2022 · Citations: 0
Automatic Metrics
Stance detection concerns automatically determining the viewpoint (i.e., in favour of, against, or neutral) of a text's author towards a target.
