most citedFin-RATE: A Real-world Financial Analytics and Tracking Evaluation Benchmark for LLMs on SEC Filings

1 citations · 1 across the 4 of their papers we have counts for

collaborators

17 papers

cs.CE20261 cited

Fin-RATE: A Real-world Financial Analytics and Tracking Evaluation Benchmark for LLMs on SEC Filings

Yidong Jiang, Junrong Chen, Eftychia Makri +7

With the increasing deployment of Large Language Models (LLMs) in the finance domain, LLMs are increasingly expected to parse complex regulatory disclosures. However, existing benc…

cs.IR2026

HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation

Hiren Madhu, Ngoc Bui, Ali Maatouk +6

Embedding geometry plays a fundamental role in retrieval quality, yet dense retrievers for retrieval-augmented generation (RAG) remain largely confined to Euclidean space. However,…

cs.AI2026

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis

Austin Feng, Andreas Varvarigos, Ioannis Panitsas +7

Modern enterprises generate vast streams of time series metrics when monitoring complex systems, known as observability data. Unlike conventional time series from domains such as c…

cs.LG2026

Reasoning through Verifiable Forecast Actions: Consistency-Grounded RL for Financial LLMs

Jialin Chen, Aosong Feng, Harshit Verma +7

Financial markets are characterized by extreme non-stationarity, low signal-to-noise ratios, and strong dependence on external information such as news, company fundamentals, and m…

cs.LG2026

Parameter-Efficient Fine-Tuning of LLMs with Mixture of Space Experts

Buze Zhang, Jinkai Tao, Zilang Zeng +4

Large Language Models (LLMs) have achieved remarkable progress, with Parameter-Efficient Fine-Tuning (PEFT) emerging as a key technique for downstream task adaptation. However, exi…

cs.CL2026

MTBench: A Multimodal Time Series Benchmark for Temporal Reasoning and Question Answering

Jialin Chen, Aosong Feng, Ziyu Zhao +7

Understanding the relationship between textual news and time-series evolution is a critical yet under-explored challenge in applied data science. While multimodal learning has gain…