3 citations · 3 across the 17 of their papers we have counts for
12 papers · 1 filter
KiranaBench: Can a Language Model Run a Neighbourhood Shop?
Bhuvan Arora, Ankita Karmakar, Chaitanya Jain +10
Large language model (LLM) agents are increasingly evaluated on long-horizon tasks, including autonomously running a business. Existing benchmarks for this setting are almost exclu…
Evaluation Awareness Beyond English: Do LLMs Act Differently When Tested in Indic Languages?
Trizal Garg, Sibayan Mitra, Arya Karanjkar +6
Large language models (LLMs) can often tell when they are being tested. This ability, known as evaluation awareness, can lead models to act more cautiously during safety evaluation…
The BatchNorm Illusion: Diagnosing Normalization Artifacts in Machine Unlearning Evaluation
Aaryaman Kalani, Murari Mandal, Dhruv Kumar +2
Approximate machine unlearning aims to remove the influence of specific training data from a trained model without retraining from scratch. We identify a previously undocumented co…
The Complexity Ceiling Benchmark: A Multi-Domain Evaluation of Sequential Reasoning Under Depth Scaling
Shubh Chapra, Dhruv Kumar, Murari Mandal +1
We introduce the Complexity Ceiling Benchmark (CCB), a controlled evaluation of how language-model reasoning decays as the number of required sequential steps grows. CCB fixes the…
FinBalance: A Multi-Document Accounting Reconciliation Benchmark
Sasank Tumpati, Devansh Agarwal, Ayush Kedia +6
Existing financial-NLP benchmarks mostly evaluate prepared artifacts such as filings, tables, or extracted values. Real accounting begins earlier: source documents must be reconcil…
PURGE: Projected Unlearning via Retain-Guided Erasure
Vedant Jawandhia, Daksh Ahuja, Ghufran Alam Siddiqui +3
We propose PURGE, a machine unlearning algorithm built on a simple but an under-exploited observation: continual learning (CL) and machine unlearning (MU) which are fundamentally d…
"I Strongly Suspect This Website Is a Scam": Benchmarking PII Leakage and Detection without Defense in Autonomous Web Agents
Soham Roy, Sarthakbrata Halder, Arya Bharaty +5
Deceptive web content, widely instantiated across the internet and commonly known as \textit{social-engineering attacks}, manipulates autonomous web agents into submitting users' p…
BITS Pilani at SemEval-2026 Task 9: Structured Supervised Fine-Tuning with DPO Refinement for Polarization Detection
Atharva Gupta, Dhruv Kumar, Yash Sinha
The POLAR SemEval-2026 Shared Task aims to detect online polarization and focuses on the classification and identification of multilingual, multicultural, and multi-event polarizat…
Beyond Accuracy: Diagnosing Algebraic Reasoning Failures in LLMs Across Nine Complexity Dimensions
Parth Patil, Dhruv Kumar, Yash Sinha +1
Algebraic reasoning remains one of the most informative stress tests for large language models, yet current benchmarks provide no mechanism for attributing failure to a specific ca…
Trust Regions Sell, But Who's Buying? Overlap Geometry as an Alternative Trust Region for Policy Optimization
Gaurish Trivedi, Alakh Sharma, Kartikey Singh Bhandari +4
Standard trust-region methods constrain policy updates via Kullback-Leibler (KL) divergence. However, KL controls only an average divergence and does not directly prevent rare, lar…
The Compliance Paradox: Semantic-Instruction Decoupling in Automated Academic Code Evaluation
Devanshu Sahoo, Manish Prasad, Vasudev Majhi +5
The rapid integration of Large Language Models (LLMs) into educational assessment rests on the unverified assumption that instruction following capability translates directly to ob…
When Reject Turns into Accept: Quantifying the Vulnerability of LLM-Based Scientific Reviewers to Indirect Prompt Injection
Devanshu Sahoo, Manish Prasad, Vasudev Majhi +5
Driven by surging submission volumes, scientific peer review has catalyzed two parallel trends: individual over-reliance on LLMs and institutional AI-powered assessment systems. Th…