activity
20242026
most citedTracing Positional Bias in Financial Decision-Making: Mechanistic Insights from Qwen2.5

3 citations · 4 across the 7 of their papers we have counts for

collaborators

11 papers

q-fin.CP2026

Deep Reinforcement Learning for Optimum Order Execution: Mitigating Risk and Maximizing Returns

Khabbab Zakaria, Jayapaulraj Jerinsh, Andreas Maier +3

Optimal Order Execution is a well-established problem in finance that pertains to the flawless execution of a trade (buy or sell) for a given volume within a specified time frame.…

q-fin.CP2025

Uncovering Representation Bias for Investment Decisions in Open-Source Large Language Models

Fabrizio Dimino, Krati Saxena, Bhaskarjit Sarmah +1

Large Language Models are increasingly adopted in financial applications to support investment workflows. However, prior studies have seldom examined how these models reflect biase…

q-fin.CP2025

FinCARE: Financial Causal Analysis with Reasoning and Evidence

Alejandro Michel, Abhinav Arun, Bhaskarjit Sarmah +1

Portfolio managers rely on correlation-based analysis and heuristic methods that fail to capture true causal relationships driving performance. We present a hybrid framework that i…

q-fin.CP2025

FinReflectKG -- MultiHop: Financial QA Benchmark for Reasoning with Knowledge Graph Evidence

Abhinav Arun, Reetu Raj Harsh, Bhaskarjit Sarmah +1

Multi-hop reasoning over financial disclosures is often a retrieval problem before it becomes a reasoning or generation problem: relevant facts are dispersed across sections, filin…

q-fin.CP2025

FINCH: Financial Intelligence using Natural language for Contextualized SQL Handling

Avinash Kumar Singh, Bhaskarjit Sarmah, Stefano Pasquali

Text-to-SQL, the task of translating natural language questions into SQL queries, has long been a central challenge in NLP. While progress has been significant, applying it to the…

q-fin.ST2025

AlphaAgents: Large Language Model based Multi-Agents for Equity Portfolio Constructions

Tianjiao Zhao, Jingrao Lyu, Stokes Jones +3

The field of artificial intelligence (AI) agents is evolving rapidly, driven by the capabilities of Large Language Models (LLMs) to autonomously perform and refine tasks with human…