2026 Question Answering System Projects | Extractive · Generative · RAG · SQuAD

Question Answering System Projects — From Passage to Answer

Question answering systems retrieve or generate answers from text. Final-year projects that implement extractive span models, generative seq2seq, RAG pipelines or multi-hop reasoning — with Exact Match and F1 metrics — produce strong, industry-relevant results.

Below are 80+ topics across extractive QA, generative QA, RAG/open-domain, multi-hop reasoning, evaluation and applications, with tools (Hugging Face, LangChain, Haystack) and datasets (SQuAD, Natural Questions, HotpotQA).

Hugging Face LangChain SQuAD Haystack Natural Questions FastAPI

#	Question Answering Project Topic	Tools · Datasets
📄 Extractive QA · Span Selection
01	ExtBERT Fine-Tuning for Extractive QA on SQuAD	Hugging Face, SQuAD
02	ExtRoBERTa / DistilBERT for Faster Extractive QA	HF Transformers
03	ExtStart–End Logit Span Prediction Pipeline	Token classification head
04	ExtHandling Unanswerable Questions (SQuAD 2.0)	Null threshold tuning
05	ExtAnswer Length and Position Bias Analysis	Error analysis
06	ExtTransfer Learning: SQuAD → Domain Documents	Fine-tune on custom text
07	ExtMulti-Passage Extractive QA Ranking	Passage ranker + reader
08	ExtLightweight Extractive QA for Edge Devices	Distilled models
09	ExtVisualisation of Attention for Answer Spans	Attention maps
10	ExtClassical IR + Reading Comprehension Pipeline	BM25 + neural reader
11	ExtCross-Lingual Extractive QA Pilot	mBERT / XLM-R
12	ExtAblation of Context Length on EM / F1	Truncation study
13	ExtEnsemble of Extractive Models	Majority / score fusion
14	ExtError Analysis: Type of Missed Answers	Taxonomy of failures
15	ExtReproducible Extractive QA Training Package	Configs, seeds, logs
✍️ Generative QA · Seq2Seq · Free-Form
16	GenT5 / BART Fine-Tuning for Generative QA	HF seq2seq models
17	GenAbstractive vs Extractive Answer Comparison	Same questions, dual outputs
18	GenPrompt-Based Generative QA with LLMs	Few-shot prompting
19	GenControlled Generation for Concise Answers	Length / style constraints
20	GenHallucination Detection in Generated Answers	Faithfulness checks
21	GenInstruction-Tuned Model for Domain QA	SFT on FAQ pairs
22	GenBeam Search vs Greedy Decoding Study	Decoding ablations
23	GenConversational QA with Context History	Multi-turn context
24	GenAnswerability Classification Before Generation	Binary filter + generator
25	GenEvaluation Beyond EM: BLEU / ROUGE for QA	Generation metrics
26	GenLightweight Generative QA with Distilled Models	Small T5 variants
27	GenPost-Editing Generated Answers for Factuality	Verification step
🔍 RAG · Open-Domain QA
28	RAGDense Passage Retrieval + Reader Pipeline	DPR concepts, HF
29	RAGLangChain RAG for Document QA	LangChain, vector store
30	RAGHybrid Retrieval: BM25 + Dense Embeddings	Fusion ranking
31	RAGChunking Strategies for Long Documents	Chunk size ablation
32	RAGCitation and Source Attribution in Answers	Retrieved doc links
33	RAGOpen-Domain QA on Wikipedia-Style Corpora	NQ / TriviaQA style
34	RAGUpdating Knowledge Base Without Retraining	Re-index pipeline
35	RAGRAG Evaluation: Retrieval Recall + Answer F1	Component metrics
36	RAGConversational RAG with Chat Memory	History + retrieval
37	RAGDomain FAQ RAG Bot (College / Product Docs)	Custom KB
38	RAGHaystack Pipeline for Production-Style QA	Haystack concepts
39	RAGLatency Optimisation of RAG Pipelines	Caching, approximate search
40	RAGComparison of Embedding Models for Retrieval	Sentence transformers
🔗 Multi-Hop · Reasoning · Complex QA
41	HopHotpotQA-Style Multi-Hop Question Answering	HotpotQA, multi-doc
42	HopSupporting Fact Identification for Multi-Hop	Sentence selection
43	HopChain-of-Thought Prompting for Complex QA	LLM reasoning traces
44	HopGraph-Based Reasoning Over Entities	Knowledge graph concepts
45	HopDecomposition of Complex Questions	Sub-question generation
46	HopEvidence Aggregation Across Documents	Multi-doc fusion
47	HopComparison of Single-Hop vs Multi-Hop Models	Same eval, dual setups
48	HopError Propagation in Multi-Step Reasoning	Step-wise analysis
49	HopTable + Text Hybrid QA Concepts	Structured + unstructured
50	HopNumerical Reasoning in QA (Math Word Problems)	DROP / arithmetic QA
📏 Evaluation · Metrics · Robustness
51	EvalExact Match and Token-Level F1 Metrics	SQuAD evaluation script
52	EvalHuman Evaluation Protocol for Answer Quality	Rubrics, Likert scales
53	EvalRobustness to Paraphrased Questions	Paraphrase test sets
54	EvalAdversarial Questions and Attack Awareness	Adversarial examples
55	EvalCalibration of Confidence Scores	Reliability diagrams
56	EvalCross-Domain Generalisation Evaluation	Train A, test B
57	EvalLatency and Throughput Benchmarks	Profiling tools
58	EvalAutomated Regression Test Suite for QA	Fixed question set
59	EvalError Taxonomy: Retrieval vs Reader Failures	Log analysis
60	EvalReproducible Evaluation Package for Course Projects	Scripts, configs
🏭 Applications · Deployment · Research
61	AppDomain FAQ Question Answering System	RAG or extractive
62	AppLegal / Policy Document QA Assistant	Long-doc retrieval
63	AppMedical Literature QA Concepts (Non-Clinical)	PubMed-style abstracts
64	AppEducational Tutoring QA Over Course Material	Lecture notes KB
65	AppCustomer Support Knowledge Base QA	Ticket / FAQ corpus
66	AppWeb API Deployment of a QA Model	FastAPI / Flask
67	AppInteractive Demo UI for Question Answering	Simple web front-end
68	AppMulti-Language QA System Pilot	Cross-lingual models
69	AppVoice Interface Wrapper for Text QA	STT + TTS
70	AppAnalytics Dashboard for QA Usage Metrics	Logs, charts
71	ResearchComparison of Extractive vs Generative vs RAG	Same domain, three stacks
72	ResearchEthical Guidelines for Student QA Projects	Privacy, bias report
73	ResearchData Annotation Best Practices for QA	Span guidelines
74	ResearchEducational Lab: Retrieve → Read → Answer → Eval	Student starter kit
75	ResearchCommon Pitfalls in Student QA Projects	Checklist design
76	ResearchOpen Datasets and Benchmarks Survey	SQuAD, NQ, HotpotQA
77	ResearchBias and Fairness in Question Answering	Demographic evaluation
78	ResearchStudent Portfolio: Live Demo + Metrics Report	Figure pipeline
79	ResearchThesis Package: Design → Implement → Evaluate → Discuss	Full documentation
80	ResearchContinuous Improvement from User Feedback	Log → retrain loop
81	ResearchMulti-Modal QA Awareness (Text + Image)	VQA concepts
82	ResearchEnd-to-End Capstone: Domain QA from Scratch to Deploy	Complete project arc

Topics use Hugging Face Transformers, LangChain, Haystack concepts and datasets SQuAD, Natural Questions, HotpotQA, TriviaQA. Contact us for reference material, code, evaluation metrics (EM, F1), university-format report, PPT and viva Q&A for any topic above.

Why Choose Us for Question Answering Projects?

Bangalore-based guidance for BE, BTech and MTech students working on extractive, generative, RAG and multi-hop QA systems.

Extractive QA

BERT-style span selection on SQuAD, unanswerable handling and domain transfer.

Generative QA

T5/BART fine-tuning, prompt-based LLM QA and hallucination awareness.

RAG / Open-Domain

Dense retrieval, hybrid search and grounded answers over document collections.

Multi-Hop

HotpotQA-style reasoning, evidence aggregation and chain-of-thought concepts.

Frequently Asked Questions — Question Answering

Top topics include extractive QA on SQuAD, generative QA with seq2seq models, RAG-based open-domain QA, multi-hop reasoning (HotpotQA style), domain FAQ systems and evaluation with Exact Match and F1.

Hugging Face Transformers, LangChain, Haystack concepts, spaCy; datasets SQuAD, Natural Questions, HotpotQA, TriviaQA and custom domain document sets.

Yes. Packages include reference material, training/inference code, evaluation metrics (EM, F1), dataset notes, university-format report, PPT and viva Q&A.

Extractive QA selects a span of text from a given passage as the answer. Generative QA produces free-form text answers, often with seq2seq or LLM models, and may combine retrieval (RAG) for open-domain settings.

Question Answering Lab — Bangalore

Extractive, generative, RAG and multi-hop QA support for BE, BTech and MTech projects.

Extractive QA
SQuAD Fine-Tune

Span Selection

Generative QA
T5 / BART

Free-Form

RAG Pipelines
LangChain

Open-Domain

Multi-Hop
HotpotQA

Reasoning

EM / F1
Evaluation

Metrics

Domain FAQ
Systems

Applications

API Deploy
FastAPI

Serving

Viva & Report
Preparation

Documentation