← Search

Md Nayem Uddin

8 accepted papers

2026

GuidedSampling: Steering LLMs Towards Diverse Candidate Solutions at Inference-Time

ICLR 2026poster

Repeated Sampling (RS) is a simple inference-time algorithm that has been shown to improve model performance on complex tasks. Although it is an effective way of scaling inference time, it often struggles to generate diverse solution candidates, frequently relying on the same underlying approach to…

Cited by 0SourcecodeScholar
2025

BEMEAE: Moving Beyond Exact Span Match for Event Argument Extraction

NAACL 2025long

Event Argument Extraction (EAE) is a key task in natural language processing, focusing on identifying and classifying event arguments in text. However, the widely adopted exact span match (ESM) evaluation metric has notable limitations due to its rigid span constraints, often misidentifying valid pr…

2025

ThinkTuning: Instilling Cognitive Reflections without Distillation

EMNLP 2025

Recent advances in test-time scaling have led to the emergence of thinking LLMs that exhibit self-reflective behaviors and multi-step reasoning. While RL drives this self-improvement paradigm, recent studies show that solely RL does not truly instill these new reasoning abilities - it merely draws o

Cited by 0SourcePDFScholar
2025

UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs’ Memorization

ACL 2025long

This paper introduces UnSeenTimeQA, a novel data contamination-free time-sensitive question-answering (TSQA) benchmark. It differs from existing TSQA benchmarks by avoiding web-searchable queries grounded in the real world. We present a series of time-sensitive event scenarios based on synthetically…

Cited by 0SourcePDFScholar
2024

Asking and Answering Questions to Extract Event-Argument Structures

COLING 2024main

This paper presents a question-answering approach to extract document-level event-argument structures. We automatically ask and answer questions for each argument type an event may have. Questions are generated using manually defined templates and generative transformers. Template-based questions ar…

2024

Chaos with Keywords: Exposing Large Language Models Sycophancy to Misleading Keywords and Evaluating Defense Strategies

ACL 2024findings

This study explores the sycophantic tendencies of Large Language Models (LLMs), where these models tend to provide answers that match what users want to hear, even if they are not entirely correct. The motivation behind this exploration stems from the common behavior observed in individuals searchin…

Cited by 6SourcePDFScholar
2024

Generating Uncontextualized and Contextualized Questions for Document-Level Event Argument Extraction

NAACL 2024long

This paper presents multiple question generation strategies for document-level event argument extraction. These strategies do not require human involvement and result in uncontextualized questions as well as contextualized questions grounded on the event and document of interest. Experimental result…

2023

Interpreting Indirect Answers to Yes-No Questions in Multiple Languages

EMNLP 2023long findings

Yes-no questions expect a yes or no for an answer, but people often skip polar keywords. Instead, they answer with long explanations that must be interpreted. In this paper, we focus on this challenging problem and release new benchmarks in eight languages. We present a distant supervision approach…

Cited by 0SourcecodeScholar