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cs.CL2026
Context-Grounding Gains Are Mediated by Pre-existing Machinery: Auditing GRPO, SFT, and DPO
Prakhar Gupta, Vaibhav Gupta
Language models can ignore prompt evidence when it conflicts with memorized knowledge. Post-training can make models follow such evidence more reliably, but it is unclear whether t…
cs.CL2024
Revisiting In-Context Learning with Long Context Language Models
Jinheon Baek, Sun Jae Lee, Prakhar Gupta +3
In-Context Learning (ICL) is a technique by which language models make predictions based on examples provided in their input context. Previously, their context window size imposed…
cs.CL2024★ 1 cited
Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions
Angana Borah, Rada Mihalcea
As Large Language Models (LLMs) continue to evolve, they are increasingly being employed in numerous studies to simulate societies and execute diverse social tasks. However, LLMs a…