GEAR: Training-Free Rule Distillation for Advanced and Efficient Tool-Augmented Reasoning.
AACL-IJCNLP 2026Mechanistic InterpretabilityNewPaper coming soon
About Me
Bhiman Kumar Baghel
PhD Student in Computer Science, University of Pittsburgh
Advised by Prof. Xiang (Lorraine) Li
My research centers on interpretable and efficient reasoning in AI.
My research centers on interpretable and efficient reasoning in AI. I aim to make AI systems more trustworthy as they increasingly shape decisions in everyday life, while also helping ensure that advanced reasoning capabilities remain broadly accessible rather than concentrated among only a few actors.
I aim to make AI systems more trustworthy as they increasingly shape decisions in everyday life, while also helping ensure that advanced reasoning capabilities remain broadly accessible rather than concentrated among only a few actors.
My work spans a spectrum from verbalized reasoning to mechanistically interpretable reasoning. This includes making AI agents more capable and efficient through inference-time rule distillation, as well as developing model editing methods that improve how factual knowledge is updated inside large language models.
Live Timeline
News
Conference presentations, milestones, and recent updates.
Aug 2026
🎉 "GEAR: Training-Free Rule Distillation for Advanced and Efficient Tool-Augmented Reasoning" was accepted as a main paper at AACL-IJCNLP 2026. Paper coming soon.
Aug 2026
🎉 Successfully completed my second Amazon internship as an Applied Scientist II Intern.
Jun 2026
🎉 "CreativityPrism: A Holistic Evaluation Framework for Large Language Model Creativity" was accepted to TMLR.
May 2026
🤖 Returned to Amazon as an Applied Scientist II Intern and moved to Seattle to work on enterprise autonomous agents.
Mar 2026
🎓 Passed my Ph.D. comprehensive exam, marking an important milestone in my doctoral journey.
Jan 2026
🎉 Completed my Amazon internship and received a return offer for Summer 2026.
Nov 2025
🇨🇳 Attended EMNLP 2025 in China and presented "Resolving UnderEdit & OverEdit with Iterative & Neighbor-Assisted Model Editing."
Oct 2025
🤖 Started as an Applied Scientist II Intern at Amazon, working on making AI agent reasoning more capable and efficient.
Aug 2025
🎉 "Resolving UnderEdit & OverEdit with Iterative & Neighbor-Assisted Model Editing" was accepted to Findings of EMNLP 2025.
Dec 2024
🎉 A1 U.S. patent application published: "Methods and systems for enabling seamless indirect interactions."
Sept 2024
👨🔬 Started as a Graduate Research Assistant at SCI, University of Pittsburgh.
Aug 2024
📽️ Gave a lightning talk on "A Fairness Analysis of Human and AI-Generated Student Reflection Summaries" at the Gender Bias in Natural Language Processing Workshop at ACL 2024.
Jul 2024
🗣️ Received an oral presentation invitation for "A Fairness Analysis of Human and AI-Generated Student Reflection Summaries" at the Gender Bias in Natural Language Processing Workshop at ACL 2024.
Jun 2024
🎉 "A Fairness Analysis of Human and AI-Generated Student Reflection Summaries" was accepted to the Gender Bias in Natural Language Processing Workshop at ACL 2024.
Jun 2024
📽️ Presented "Multimodal Understanding of Memes with Fair Explanations" at the MULA Workshop at CVPR 2024.
May 2024
🗣️ Received an oral presentation invitation for "Multimodal Understanding of Memes with Fair Explanations" at the MULA Workshop at CVPR 2024.
Mar 2024
🎉 "Multimodal Understanding of Memes with Fair Explanations" was accepted to the MULA Workshop at CVPR 2024.
Feb 2024
🎉 A1 U.S. patent application published: "Method and system for mitigating physical risks in an IoT environment."
Feb 2024
🤩 Selected to attend Google Research Week.
Jan 2024
👨🏫 Started as a Teaching Assistant for Intro to NLP at SCI, University of Pittsburgh.
Sep 2023
👨🏫 Started as a Teaching Assistant for Operating Systems at SCI, University of Pittsburgh.
Aug 2023
🎓 Started my Ph.D. in Computer Science at the University of Pittsburgh.
Mar 2023
🆙 Promoted to Lead Engineer, NLP, at Samsung Research Institute Bangalore.
Mar 2023
🏆 Received the Samsung Excellence Award at Samsung Research Institute Bangalore.
Mar 2023
🎉 A1 U.S. patent application published: "Methods and systems for determining missing slots associated with a voice command for an advanced voice interaction."
Mar 2023
🌟 Received the MBO High Performance Bonus at Samsung Research Institute Bangalore.
Sep 2022–Dec 2022
✈️ Traveled to Samsung HQ in South Korea to lead a project that developed COSMIC, a multi-intent smart home assistant.
Primary Research Record
Publications
Peer-reviewed work and archival publications spanning mechanistic interpretability, AI fairness, conversational AI, and AI creativity.
Browse by topic
2026
CreativityPrism: A Holistic Evaluation Framework for Large Language Model Creativity.
Zhaoyi Joey Hou, Bowei Alvin Zhang, Yining Lu, Bhiman Kumar Baghel, Anneliese Brei, Ximing Lu, Meng Jiang, Faeze Brahman, Snigdha Chaturvedi, Haw-Shiuan Chang, Daniel Khashabi, Xiang Lorraine Li
2025
Resolving UnderEdit & OverEdit with Iterative & Neighbor-Assisted Model Editing.
Bhiman Kumar Baghel, Emma Jordan, Zheyuan Ryan Shi, Xiang Lorraine Li
2024
2021
Intent Focused Semantic Parsing and Zero-Shot Learning for Out-of-Domain Detection in Spoken Language Understanding.
Niraj Kumar, Bhiman Kumar Baghel
This work addresses zero-shot out-of-domain detection in spoken language understanding, where manually labeled OOD data is unavailable. It combines sentence-level intents and token-level intent classes from intent-focused semantic parsing with a one-class neural network classifier, achieving stronger performance than prior methods across four public datasets.
Smart Stacking of Deep Learning Models for Granular Joint Intent-Slot Extraction for Multi-Intent SLU.
Niraj Kumar, Bhiman Kumar Baghel
This work tackles fine-grained multi-intent spoken language understanding, where systems must jointly identify intents and slots while modeling their local relationships at both token and utterance levels. It proposes a smart stacking ensemble built on BERT, XLNet, and ELMo multitask models, outperforming prior multi-intent systems on four public datasets at both sentence and token levels.
Research and Industry
Experience
Recent work across academia and industry, with emphasis on research contributions, systems impact, and model behavior.
Amazon
Applied Scientist II Intern
May 2026 – August 2026Seattle, WA, USA
- Working on enterprise autonomous agents.
Amazon
Applied Scientist II Intern
October 2025 – January 2026Seattle, WA, USA
- Worked on making AI agent reasoning more capable and efficient through inference-time rule distillation.
University of Pittsburgh
Graduate Research Assistant
August 2024 – PresentPA, USA
- Engineered a plug-and-play iterative editing pipeline that enhanced edit-success rate by 38 percentage points over prior SOTA on LLaMA-3/2 and GPT-J, enabling rapid knowledge updates without full-model fine-tuning
- Developed a Shapley- and cartography-based framework to identify influential training examples, revealing key differences in generalization behavior of LoRA on legal reasoning tasks compared to other tuning methods
- Conducted a gender-bias audit of GPT-3.5 and BART summaries over 19,579 student reflections; used Jensen–Shannon divergence to reveal a 10% male-topic skew and uncovered under-represented female topics
- Built a 2,900-meme multimodal dataset; manual audit revealed stereotype bias in 40% of LLaVA and MiniGPT-4 explanations, traced to visual/named-entity stereotypes, and text–image representation imbalance
Samsung Research
Lead NLP Engineer
June 2019 – August 2023Bangalore, India
- Spearheaded CoSMIC, a BERT-based multi-intent NLU engine for SmartThings; shipped to 100M+ devices, reaching 96% intent accuracy and cutting live NLU errors by 67%
- Localized and scaled CoSMIC for the Korean market, mentoring a cross-site team and re-engineering tokenization to lift intent-slot F₁ by 25%
- Architected production conversational-AI models (intent, slot, OOD) that raised multi-intent F₁ from 87% → 92% and achieved 90% OOD recall across all public benchmarks
IBM
Machine Learning Intern
May 2018 – July 2018Bangalore, India
- Prototyped an LSTM-based anomaly-prediction engine that monitors 33 infrastructure health metrics and launches auto-remediation scripts, forecasting critical failures with 97% precision
Academic Background
Education
Training, degrees, and academic mentorship across institutions.
University Of Pittsburgh, PA, USA
PhD in Computer ScienceGPA 3.5/5
August 2023 - April 2027
Advisor: Dr. Xiang (Lorraine) Li
Indian Institute of Technology (IIT), Kharagpur, India
M.Tech in Computer ScienceGPA 8.82/10
July 2017 - May 2019
Thesis: DCLL - A Deep Learning Model for Travel Time and Traffic Congestion Prediction
National Institute Of Technology (NIT), Jalandhar, India
B.Tech in Computer ScienceGPA 6.82/10
June 2013 - June 2017
Applied AI
Patents
Patent work and production-facing research connected to conversational AI, IoT, and personalization.
Method and system for time based personalization management in multi-device environment
Samsung Research • WO2025018568A1
Patent work on personalization and orchestration across connected devices.
Methods and systems for enabling seamless indirect interactions.
Samsung Research • US 18517995
Systems research focused on multimodal and indirect interaction flows.
Method and system for mitigating physical risks in an IoT environment.
Samsung Research • US 18202687
Applied ML for risk mitigation and decision support in IoT settings.
Methods and systems for determining missing slots associated with a voice command for an advanced voice interaction.
Samsung Research • US 17835387
Conversational AI patent work on slot completion and voice interaction quality.
Recognition
Honors
Selected awards and recognitions across research and industry.
2023
Samsung High Performance Bonus (3×)
Samsung Research -- Bangalore, India
2023
Samsung Excellence Award (5×)
Samsung Research -- Bangalore, India
Recognized for SmartThings CLab innovation finalist and 4 US A1 patent filings.
2018
2nd Runner-Up, Audience Poll
IBM Extreme Blue Expo -- Bangalore, India
Voted top-3 of 24 projects by 100+ expo attendees.