<div dir="auto">Hi Everyone,</div><div dir="auto"><br></div><div dir="auto">The first meetup for the Spring quarter will be led by Arman Irani, please see details below.<br clear="all"><br clear="all"><div dir="auto"><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature">Cheers,</div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature">Emiliano</div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><br></div><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="auto"><span style="font-family:-apple-system,"helvetica neue";font-size:1rem;font-style:normal;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)">TITLE</span></div><div dir="auto"><span style="font-family:-apple-system,"helvetica neue";font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;float:none;display:inline!important;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)">Embedded Biases: The Impact of Cognitive Biases on Argument Similarity</span><br style="color:rgb(212,212,213);font-family:'-apple-system','helvetica neue';font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none"><div style="font-family:-apple-system,"helvetica neue";font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)" dir="auto"><br></div><div style="font-family:-apple-system,"helvetica neue";font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)" dir="auto">SPEAKER</div><div style="font-family:-apple-system,"helvetica neue";font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)" dir="auto">Arman Irani, PhD Candidate at UCR</div><div style="font-family:-apple-system,"helvetica neue";font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)" dir="auto"><br></div><div style="font-family:-apple-system,"helvetica neue";font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)" dir="auto">WHERE/WHEN</div><div style="font-family:-apple-system,"helvetica neue";font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)" dir="auto">Wed, April 2nd, 2pm</div><div style="font-family:-apple-system,"helvetica neue";font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)" dir="auto"><div dir="auto" style="font-family:-apple-system,"helvetica neue""><span style="font-family:-apple-system,helveticaneue;font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration:none;float:none;display:inline!important;background-color:rgba(0,0,0,0);border-color:rgb(0,0,0);color:rgb(0,0,0)">In Person: WCH 203  </span></div><div dir="auto" style="font-family:-apple-system,"helvetica neue""><span style="font-family:-apple-system,helveticaneue;font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;text-decoration:none;float:none;display:inline!important;background-color:rgba(0,0,0,0);border-color:rgb(0,0,0);color:rgb(0,0,0)">Zoom: </span><a href="https://ucr.zoom.us/j/92699528206?pwd=oo5ujmYE79Wqywca0CaaQBd1WAhUFz.1" style="font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:0px;font-family:-apple-system,helveticaneue;background-color:rgba(0,0,0,0);border-color:rgb(66,133,244);color:rgb(66,133,244)">link</a></div></div><div style="font-family:-apple-system,"helvetica neue";font-size:15px;font-style:normal;font-weight:400;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)" dir="auto"><br></div><div style="font-family:-apple-system,"helvetica neue";font-size:1rem;font-style:normal;letter-spacing:normal;text-indent:0px;text-transform:none;white-space:normal;word-spacing:1px;text-decoration:none;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)" dir="auto"><span style="font-family:-apple-system,"helvetica neue";font-size:1rem;background-color:rgba(0,0,0,0);border-color:rgb(49,49,49);color:rgb(49,49,49)">ABSTRACT</span><br>How can we determine argument similarity by focusing on foundational positional rhetoric rather than being misled by surface-level semantic resemblances? Humans naturally conflate argument similarity based on framing, wording, and emotional resonance. Consequently, these cognitive biases likely permeate training corpora that are the underlying foundation of modern text embedding models, perpetuating superficial similarity assessments rather than capturing deeper positional alignments. This work systematically applies a cognitive bias framework to explain embedding models' vulnerability to incorrectly assessing positional argument similarity. We contribute (1) a novel dataset of 8,000 argument pairs for evaluating and benchmarking positional argument similarity, (2) a comprehensive assessment of popular text embedding models vulnerability to cognitive bias misalignment, and (3) effective debiasing interventions. Our cognitive science approach provides post-hoc interpretability for black-box text embedding model misjudgments. Through this interdisciplinary lens, we demonstrate how cognitive science theories can enhance positionally-aware argument similarity assessment in computational argumentation, highlighting critical areas for future development.</div></div></div></div></div>