Get started
Author

Dan Roth

Devil’s Advocate: Anticipatory Reflection for LLM Agents
2024 · Haoyu Wang, Tao Li, et al. · Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP) · 6
PDF
On Learning Latent Models with Multi-Instance Weak Supervision
2023 · Kaifu Wang, Efthymia Tsamoura, et al. · neural information processing systems · 3
PDF
Weaver: Interweaving SQL and LLM for Table Reasoning
2025 · Rohit Khoja, Devanshu Gupta, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 2
PDF
When Vision-Language Models Judge Without Seeing: Exposing Informativeness Bias
2026 · Xiaohan Zou, Roshan Sridhar, et al. · Proceedings of the conference - Association for Computational Linguistics. Meeting · 1
PDF
Enhancing Temporal Understanding in LLMs for Semi-structured Tables
2025 · Irwin Deng, Kushagra Dixit, et al. · Findings of the Association for Computational Linguistics: NAACL · 1
PDF
Prefix Executability: Evaluating Tool-Using Agents Beyond Final Success
2026 · Rezaeian, Amir H., Sun, Weiyi, et al. · arXiv (Cornell University)
PDF
VELD-QA: A Large-Scale Dataset for Visual Evidence Grounding and Question Answering in Long Documents
2026 · Sourati, Zhivar, Liu, Marianne Menglin, et al. · arXiv (Cornell University)
PDF
ExperienceIndex: Artifact-Grounded Memory
2026 · Chen, Peter Baile, Yu, Geoffrey X., et al. · arXiv (Cornell University)
PDF
Is Code Better Than Language for Algorithmic Reasoning
2026 · Tong, Terry, Feng, Yu, et al. · arXiv (Cornell University)
PDF
SOMA-SQL: Resolving Multi-Source Ambiguity in NL-to-SQL via Synthetic Log and Execution Probing
2026 · Somayajula, Sai Ashish, Liu, Marianne Menglin, et al. · arXiv (Cornell University)
PDF
Do Image-Text Metrics Respect Semantic Invariances?
2026 · Agarwal, Amit, Patel, Hitesh Laxmichand, et al. · arXiv (Cornell University)
PDF
GSM-SEM: Benchmark and Framework for Generating Semantically Variant Augmentations
2026 · Singh, Jyotika, Tu, Fang, et al. · arXiv (Cornell University)
PDF
SPENCE: A Syntactic Probe for Detecting Contamination in NL2SQL Benchmarks
2026 · Safarzadeh, Mohammadtaher, Patel, Hitesh Laxmichand, et al. · arXiv (Cornell University)
PDF
When Vision-Language Models Judge Without Seeing: Exposing Informativeness Bias
2026 · Zou, Xiaohan, Sridhar, Roshan, et al. · arXiv (Cornell University)
PDF
MT-OSC: Path for LLMs that Get Lost in Multi-Turn Conversation
2026 · Singh, Jyotika, Tu, Fang, et al. · arXiv (Cornell University)
PDF
DiffuMask: Diffusion Language Model for Token-level Prompt Pruning
2026 · Zheng, Caleb, Singh, Jyotika, et al. · arXiv (Cornell University)
PDF
PAR$^2$-RAG: Planned Active Retrieval and Reasoning for Multi-Hop Question Answering
2026 · Li, Xingyu, Wang, Rongguang, et al. · arXiv (Cornell University)
PDF
DataProphet: Demystifying Supervision Data Generalization in Multimodal LLMs
2026 · Qi, Xuan, He, Luxi, et al. · arXiv (Cornell University)
PDF
LLM NL2SQL Robustness: Surface Noise vs. Linguistic Variation in Traditional and Agentic Settings
2026 · Tu, Lifu, Wang, Rongguang, et al. · arXiv (Cornell University)
PDF
Think Twice Before You Write -- an Entropy-based Decoding Strategy to Enhance LLM Reasoning
2026 · He, Jiashu, Liu, Meizhu, et al. · arXiv (Cornell University)
PDF
Chart-RL: Generalized Chart Comprehension via Reinforcement Learning with Verifiable Rewards
2026 · Zhang, Xin, Li, Xingyu, et al. · arXiv (Cornell University)
PDF
AI+HW 2035: Shaping the Next Decade
2026 · Chen, Deming, Cong, Jason, et al. · arXiv (Cornell University)
PDF
SAGE: Structure Aware Graph Expansion for Retrieval of Heterogeneous Data
2026 · Titiya, Prasham, Khoja, Rohit, et al. · arXiv (Cornell University)
PDF
On Improving Neurosymbolic Learning by Exploiting the Representation Space
2026 · Naik, Aaditya, Tsamoura, Efthymia, et al. · arXiv (Cornell University)
PDF
Budget-Aware Anytime Reasoning with LLM-Synthesized Preference Data
2026 · Zhang, Xuanming, Ashrafi, Shwan, et al. · arXiv (Cornell University)
PDF
Works count: 42
Citation count: 13
H-index: 2
I10-index:
Year
Topic
Type